- calcAdaptation(BrainPart) - Method in class boone.Trainer
-
Calculates the adaptation value based on the gradient.
- calcAdaptation(BrainPart) - Method in class boone.training.AdamTrainer
-
Calculates the Adam adaptation using estimated first and second moments of the gradient.
- calcAdaptation(BrainPart) - Method in class boone.training.BackpropTrainer
-
Calculates the adaptation value being simply the gradient.
- calcAdaptation(BrainPart) - Method in class boone.training.HebbTrainer
-
Not used.
- calcAdaptation(BrainPart) - Method in class boone.training.HopfieldDeltaTrainer
-
Calculates the adaptation value based on the gradient.
- calcAdaptation(BrainPart) - Method in class boone.training.RMSpropTrainer
-
Calculates the RMSprop adaptation using a moving average of the squared gradient.
- calcAdaptation(BrainPart) - Method in class boone.training.RpropTrainer
-
Calculates the adaptation value according to Rprop.
- calcAdaptation(BrainPart) - Method in class boone.training.SAETrainer
-
Not used.
- calcAdaptation(BrainPart) - Method in class boone.training.SOMTrainer
-
Not used.
- calcLimit(Function, int, double) - Method in class boone.util.RootSolver
-
Calculates the point at which the specified function will fall below a given bound.
- calcOrder - Variable in class boone.structure.NetCompiler.BooneCompiledNet
-
Calculation order.
- calculate() - Method in class boone.BrainPart
-
Calculate the current state of this brain part.
- calculate() - Method in class boone.Neuron
-
Propagate the neuron input to the neuron output.
- calculate() - Method in class boone.neurons.MaxPoolNeuron
-
Calculates the neuron output based on its input, which is the maximal signal.
- calculate() - Method in class boone.spike.SpikingLink
-
Generate a new SpikeEvent with timestamp set to value + delay, with type SpikeEvent.POST_SPIKE, and origin and destination
set to this links source and sink neuron respectively.
- calculate() - Method in class boone.spike.SpikingNeuron
-
Handle the most recent event scheduled by the SpikingNeuralNet to which this neuron belongs.
- calculateNeuron(int) - Method in class boone.structure.NetCompiler.BooneCompiledNet
-
Calculate the given neuron.
- CatmullRomSpline() - Constructor for class boone.map.Function.CatmullRomSpline
-
Create a new instance.
- CatmullRomSpline(double[]) - Constructor for class boone.map.Function.CatmullRomSpline
-
Create a new instance, with the given spline coefficients.
- ClassHelper - Class in boone.util
-
Helper for handling classes.
- ClassHelper() - Constructor for class boone.util.ClassHelper
-
- clear() - Method in class boone.spike.SpikeEventBuffer
-
Atomically removes all of the elements from this queue.
- clearMap() - Method in class boone.map.HexagonTopology
-
Clears the map (set to EMPTY).
- clearMap() - Method in class boone.map.Topology
-
Clears the distance map (set to EMPTY).
- clearNets() - Method in class boone.Brain
-
Clear the list of neural networks, i.e.
- clearSets() - Method in class boone.Brain
-
Clear the list of data set, i.e.
- clearSink() - Method in class boone.Link
-
Sets the sink to null.
- clearSource() - Method in class boone.Link
-
Sets the source to null.
- Clip() - Constructor for class boone.map.Function.Clip
-
- Clip(double, double) - Constructor for class boone.map.Function.Clip
-
- clone() - Method in class boone.Brain
-
Clone this Brain.
- clone() - Method in class boone.BrainPart
-
Returns a shallow copy.
- clone() - Method in class boone.Link
-
Returns a semi-deep copy of this object.
- clone() - Method in class boone.links.MaxPoolLink
-
Returns a semi-deep copy of this object.
- clone() - Method in class boone.links.MultiLink
-
Returns a semi-deep copy of this object.
- clone() - Method in class boone.map.Function.CatmullRomSpline
-
- clone() - Method in class boone.map.Function
-
Return a deep copy of this object.
- clone() - Method in class boone.map.Function.Composition
-
- clone() - Method in class boone.map.Function.NaturalSpline
-
- clone() - Method in class boone.map.Function.Scaled
-
- clone() - Method in class boone.map.HexagonTopology
-
A deep clone.
- clone() - Method in class boone.map.Position
-
Returns a shallow clone.
- clone() - Method in class boone.map.Topology
-
A clone keeping the reference to the same network and the same neighbor list.
- clone() - Method in class boone.NeuralNet
-
Clone method for this NeuralNet.
- clone() - Method in class boone.Neuron
-
Returns a semi-deep clone of this neuron.
- clone() - Method in class boone.neurons.MaxPoolNeuron
-
Returns a semi-deep clone of this neuron.
- clone() - Method in class boone.PatternSet
-
Creates a (nearly) deep copy of this data set.
- clone() - Method in class boone.spike.NeuronPotential
-
Returns a deep copy of this NeuronPotential.
- clone() - Method in class boone.spike.PostsynapticPotential
-
- clone() - Method in class boone.spike.Spike
-
- clone() - Method in class boone.spike.SpikeEvent
-
Return a shallow copy of this SpikeEvent.
- clone() - Method in class boone.spike.SpikeSet
-
Returns a deep clone of the spike set.
- clone() - Method in class boone.spike.SpikingLink
-
- clone() - Method in class boone.spike.SpikingNeuron
-
- clone() - Method in class boone.structure.ConvolutionMap
-
Returns a semi-deep clone of this map.
- clone() - Method in class boone.structure.ForwardMap
-
Returns a shallow clone of this map.
- clone() - Method in class boone.structure.Map
-
Returns a semi-deep clone of this map.
- clone() - Method in class boone.Trainer
-
Return a deep clone of this object.
- clone() - Method in class boone.training.LVQTrainer
-
A deep clone.
- clone() - Method in class boone.training.SOMTrainer
-
A deep clone.
- clone() - Method in class boone.training.TrainingSignalGenerator
-
Return a deep copy.
- CloneException - Exception in boone.util
-
Runtime exception to be thrown if cloning fails.
- CloneException() - Constructor for exception boone.util.CloneException
-
- CloneException(String) - Constructor for exception boone.util.CloneException
-
- CloneException(Throwable) - Constructor for exception boone.util.CloneException
-
- CloneException(String, Throwable) - Constructor for exception boone.util.CloneException
-
- colors - Variable in class boone.util.UMatrix
-
- commentStart - Variable in class boone.util.StreamParser
-
a line comment indicator: rest of the line after this is to be ignored.
- Common - Class in boone.util
-
A collection of commonly useful methods.
- Common() - Constructor for class boone.util.Common
-
- compareTo(Object) - Method in class boone.Neuron
-
Compares the neurons with respect to the layer number.
- compareTo(SpikeEvent) - Method in class boone.spike.SpikeEvent
-
Compare this SpikeEvent with the specified SpikeEvent.
- compile(NeuralNet) - Method in class boone.structure.NetCompiler.BooneCompiledNet
-
Compile the given network into this compiled net.
- compile(NeuralNet) - Static method in class boone.structure.NetCompiler
-
- compile(NeuralNet) - Method in interface boone.structure.NetCompiler.CompiledNet
-
Compile the given NeuralNet to this CompiledNet instance.
- compile(NeuralNet) - Method in class boone.structure.NeuralNetCompiler
-
- CompiledNeuralNet - Class in boone.structure
-
Advanced neural net representation.
- CompiledNeuralNet() - Constructor for class boone.structure.CompiledNeuralNet
-
- CompileException() - Constructor for exception boone.structure.NetCompiler.CompileException
-
- CompileException(String) - Constructor for exception boone.structure.NetCompiler.CompileException
-
- CompileException(Throwable) - Constructor for exception boone.structure.NetCompiler.CompileException
-
- CompileException(String, Throwable) - Constructor for exception boone.structure.NetCompiler.CompileException
-
- CompileException() - Constructor for exception boone.structure.NeuralNetCompiler.CompileException
-
- CompileException(String) - Constructor for exception boone.structure.NeuralNetCompiler.CompileException
-
- CompileException(String, Throwable) - Constructor for exception boone.structure.NeuralNetCompiler.CompileException
-
- CompileException(Throwable) - Constructor for exception boone.structure.NeuralNetCompiler.CompileException
-
- Composition() - Constructor for class boone.map.Function.Composition
-
- Composition(Function, Function) - Constructor for class boone.map.Function.Composition
-
- compressed - Variable in class boone.io.IOFilter
-
Indicates file compression.
- computeError(NeuralNet, List<Double>, List<Double>) - Method in class boone.training.CrossEntropy
-
Computes the cross entropy at the output layer for the given pattern.
- computeError(NeuralNet, List<Double>, List<Double>) - Method in class boone.training.SquareError
-
Computes the sum of squared errors at the output layer for the given pattern.
- computeError(NeuralNet, List<Double>, List<Double>) - Method in class boone.training.TrainingSignalGenerator
-
Computes the error at the output layer for the given input.
- computeErrorSignal(NeuralNet, List<Double>, List<Double>) - Method in class boone.training.CrossEntropy
-
Computes and sets the error signal for each output neuron to target / output.
- computeErrorSignal(NeuralNet, List<Double>, List<Double>) - Method in class boone.training.SquareError
-
Computes and sets the error signal for each output neuron to (output - target).
- computeErrorSignal(NeuralNet, List<Double>, List<Double>) - Method in class boone.training.TrainingSignalGenerator
-
Computes the error signal at the output layer for back-propagation.
- connect(Map) - Method in class boone.structure.FilterMap
-
Connects this map with the given previous map using the given link type for the filter.
- connect(Map) - Method in class boone.structure.ForwardMap
-
Connects each neuron (sink) of this map with each neuron of the given map (source)
using the link type of this map.
- connect(Layer) - Method in class boone.structure.Layer
-
Connects this layer with the given layer.
- connect(Layer) - Method in class boone.structure.Map
-
Connects this map with the given layer using the link type of this map.
- connect(Map) - Method in class boone.structure.Map
-
Connects this map with the given map using the link type of this map.
- connect(Layer) - Method in class boone.structure.PoolingLayer
-
Connects this layer with the given layer.
- connectedFilters - Variable in class boone.structure.FilterMap
-
The number of filters currently connected to previous layer.
- CONNECTION_SECTION_TITLE - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- constructDoubleList(double[]) - Static method in class boone.util.Conversion
-
convert an array of doubles to a String list
- constructDoubleList(List<Double>) - Static method in class boone.util.Conversion
-
convert a list of doubles to a String list
- containsClassName(String, String, char) - Static method in class boone.util.ClassHelper
-
Checks if the given name is the name of a class in path.
- Conversion - Class in boone.util
-
Various methods for conversion of data.
- Conversion() - Constructor for class boone.util.Conversion
-
- ConvolutionLayer - Class in boone.structure
-
A convolution layer.
- ConvolutionLayer() - Constructor for class boone.structure.ConvolutionLayer
-
Constructs an empty convolution layer with all zero values and default neurons and links.
- ConvolutionLayer(int, int, int, int) - Constructor for class boone.structure.ConvolutionLayer
-
Constructs a convolution layer with parameters having identical width and height, a default ReLU neuron, and a default link.
- ConvolutionLayer(int, int, int, int, Neuron, Link) - Constructor for class boone.structure.ConvolutionLayer
-
Constructs a convolution layer with parameters having identical width and height, and given neuron and link type.
- ConvolutionLayer(int, int, int, int, int, int, int, Neuron, Link) - Constructor for class boone.structure.ConvolutionLayer
-
Constructs a general convolution layer.
- ConvolutionMap - Class in boone.structure
-
A convolution map.
- ConvolutionMap(int, int, int, int, int, int, Neuron, Link) - Constructor for class boone.structure.ConvolutionMap
-
Constructs a general convolution layer.
- ConvolutionMap(Map) - Constructor for class boone.structure.ConvolutionMap
-
Constructs a map copy.
- copyTo(double[], List<Double>) - Static method in class boone.util.Conversion
-
Copies the content of the specified double array into a Double list.
- create(String) - Static method in class boone.map.Function
-
Create a function, given its name.
- createClassByName(String) - Static method in class boone.util.ClassHelper
-
Returns a class by its name inclusively the primitive types and arrays of primitive types, e.g., int[].
- createFeedForward(int[], boolean, Trainer, Neuron, Link) - Static method in class boone.structure.NetFactory
-
Create a standard feed-forward network.
- createFeedForward(List<Layer>, Trainer, boolean) - Static method in class boone.structure.NetFactory
-
Creates a feed-forward network with connections between neighboring layers.
- createFeedForward(int[], boolean, SpikingNeuron, SpikingLink) - Static method in class boone.structure.NetFactory
-
Create a feed-forward spiking net.
- createFilter() - Method in class boone.structure.FilterMap
-
Creates the filter.
- createHopfield(int, Function, Trainer, Neuron, Link) - Static method in class boone.structure.NetFactory
-
Creates a a Hopfield network, where each neuron is connected to every other.
- createHopfield(int, Function, Function, Trainer, Neuron, Link) - Static method in class boone.structure.NetFactory
-
Create a recurrent spiking neural network (e.g.
- createInputStream() - Method in class boone.io.IOFilter
-
Creates an input stream for reading from data file.
- createOutputStream() - Method in class boone.io.IOFilter
-
Creates an output stream for writing to data file.
- createRowMatrix(PatternSet) - Static method in class boone.util.JamaHelper
-
Create a matrix from the given patterns, where each row is an input pattern.
- createSOM(SOMTrainer, PatternSet) - Static method in class boone.structure.NetFactory
-
The master method for creating a SOM net.
- CrossEntropy - Class in boone.training
-
The square error function is the default for training.
- CrossEntropy() - Constructor for class boone.training.CrossEntropy
-
- CSVPatternFilter - Class in boone.io
-
The CSV pattern filter assumes that a complete pattern (input and target) is written in a single line (a record), where the
values are separated by a specific character (default is the comma ',').
- CSVPatternFilter(int, int) - Constructor for class boone.io.CSVPatternFilter
-
Constructs the CSV pattern filter with a comma separator and no header.
- CSVPatternFilter(char, int, int, boolean, int) - Constructor for class boone.io.CSVPatternFilter
-
Constructs the CSV pattern filter.
- CTYPE - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- curChar - Variable in class boone.util.StreamParser
-
the current character that was read from the stream.
- currentEpoch - Variable in class boone.Trainer
-
The current epoch during training.
- cutHeadAtLast(String, char) - Static method in class boone.util.Common
-
Eliminates the substring before the last occurrence of 'c'
including 'c'.
- cutLeadChar(String, char) - Static method in class boone.util.Common
-
Eliminates the potential leading char 'c' in string 's'.
- cutTailAtLast(String, char) - Static method in class boone.util.Common
-
Eliminates the substring after the last occurrence of 'c'
including 'c'.
- f - Variable in class boone.map.Function.Composition
-
- FEEDFORWARD - Static variable in class boone.NeuralNet
-
A feed-forward network.
- FeedForwardLayer - Class in boone.structure
-
A feed-forward (classification) layer.
- FeedForwardLayer() - Constructor for class boone.structure.FeedForwardLayer
-
Constructs an empty layer.
- FeedForwardLayer(int) - Constructor for class boone.structure.FeedForwardLayer
-
Constructs a generic 1D (standard) layer with undefined neuron type.
- FeedForwardLayer(int, Neuron, Link) - Constructor for class boone.structure.FeedForwardLayer
-
Constructs a generic 1D layer with a given neuron type.
- FeedForwardLayer(int, int, int) - Constructor for class boone.structure.FeedForwardLayer
-
Constructs a generic 3D layer with default neuron and link type.
- FeedForwardLayer(int, int, int, Neuron, Link) - Constructor for class boone.structure.FeedForwardLayer
-
Constructs a forward layer with a given neuron and link type.
- FF_LEARNING_FUNCTION - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- file - Variable in class boone.io.IOFilter
-
The IO file.
- fileHeader() - Method in class boone.io.SNNSNetFilter.ENSNNSParser
-
file_header ::= WHITESPACE COMMENT h_snns EOL COMMENT h_generated_at EOL
COMMENT h_network_name EOL COMMENT h_source_files EOL
COMMENT h_no.of_unites EOL COMMENT h_no.of_connections EOL
COMMENT h_no.of_unit_types EOL COMMENT h_no.of_site_types EOL
COMMENT h_learning_function EOL COMMENT h_update_function EOL
COMMENT h_pruning_function EOL
COMMENT ff_learning_function EOL
- filter - Variable in class boone.NeuralNet
-
The IO filter.
- filter - Variable in class boone.PatternSet
-
The data IO filter (default Boone).
- filterHeight - Variable in class boone.structure.FilterMap
-
The height of the filter.
- FilterMap - Class in boone.structure
-
A filter map.
- filters - Variable in class boone.structure.FilterMap
-
The filter bank.
- filterWidth - Variable in class boone.structure.FilterMap
-
The width of the filter.
- findRoot(Function, double, double) - Method in class boone.util.RootSolver
-
Searches for the first root r inside the specified interval such that f'(r) >= 0.
- fire(double) - Method in class boone.spike.SpikingNeuron
-
Generate a new spike with the specified firing time.
- firstCommentChar - Variable in class boone.util.StreamParser
-
- fixedPoint - Static variable in class boone.util.Common
-
For numbers with four fraction digits.
- ForwardMap - Class in boone.structure
-
A feed-forward map.
- ForwardMap(Map) - Constructor for class boone.structure.ForwardMap
-
Constructs a map copy.
- ForwardMap(int) - Constructor for class boone.structure.ForwardMap
-
Generates a quadratic forward map of given width with default neurons and links.
- ForwardMap(int, int, Neuron, Link) - Constructor for class boone.structure.ForwardMap
-
Constructs a forward map with given neurons and links.
- fromXML(Element) - Method in class boone.Brain
-
- fromXML(Element) - Method in class boone.BrainPart
-
Reads attributes from XML tree.
- fromXML(Element) - Method in interface boone.io.Storable
-
Reads attributes from XML tree.
- fromXML(Element, NeuralNet) - Method in class boone.Link
-
Reads attributes from XML tree.
- fromXML(Element, NeuralNet) - Method in class boone.links.MultiLink
-
Reads attributes from XML tree.
- fromXML(Element) - Method in class boone.map.Function.AboutEqual
-
- fromXML(Element) - Method in class boone.map.Function.AtLeast
-
Reads attribute from XML.
- fromXML(Element) - Method in class boone.map.Function.AtMost
-
Reads attribute from XML.
- fromXML(Element) - Method in class boone.map.Function.CatmullRomSpline
-
- fromXML(Element) - Method in class boone.map.Function.Clip
-
- fromXML(Element) - Method in class boone.map.Function.Composition
-
- fromXML(Element) - Method in class boone.map.Function
-
- fromXML(Element) - Method in class boone.map.Function.GreaterThan
-
- fromXML(Element) - Method in class boone.map.Function.LessThan
-
- fromXML(Element) - Method in class boone.map.Function.NaturalSpline
-
- fromXML(Element) - Method in class boone.map.Function.Scaled
-
- fromXML(Element) - Method in class boone.map.Function.Sinus
-
- fromXML(Element) - Method in class boone.map.HexagonTopology
-
- fromXML(Element) - Method in class boone.map.Position
-
Reads specific attributes from XML tree.
- fromXML(Element) - Method in class boone.NeuralNet
-
Loads the network attributes from XML.
- fromXML(Element) - Method in class boone.Neuron
-
Reads attributes from XML tree.
- fromXML(Element) - Method in class boone.neurons.NeuronList
-
- fromXML(Element) - Method in class boone.PatternSet
-
Reads patterns from XML tree.
- fromXML(Element) - Method in class boone.spike.PostsynapticPotential
-
- fromXML(Element) - Method in class boone.spike.Spike
-
- fromXML(Element, NeuralNet) - Method in class boone.spike.SpikingLink
-
Reads attributes from XML tree.
- fromXML(Element) - Method in class boone.spike.SpikingNeuralNet
-
Loads the network attributes from XML.
- fromXML(Element) - Method in class boone.spike.SpikingNeuron
-
Reads attributes from XML tree.
- fromXML(Element) - Method in class boone.structure.Layer
-
Reads attributes from XML tree.
- fromXML(Element) - Method in class boone.Trainer
-
Reads attributes from XML.
- fromXML(Element) - Method in class boone.training.AdamTrainer
-
Reads attributes from XML.
- fromXML(Element) - Method in class boone.training.HebbTrainer
-
- fromXML(Element) - Method in class boone.training.HopfieldDeltaTrainer
-
- fromXML(Element) - Method in class boone.training.LVQTrainer
-
- fromXML(Element) - Method in class boone.training.RMSpropTrainer
-
Reads attributes from XML.
- fromXML(Element) - Method in class boone.training.RpropTrainer
-
Reads attributes from XML.
- fromXML(Element) - Method in class boone.training.SOMTrainer
-
Reads attributes from XML.
- fromXML(Element) - Method in class boone.training.TrainingSignalGenerator
-
- FUNC - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- Function - Class in boone.map
-
A function that generates an output value from input values.
- Function() - Constructor for class boone.map.Function
-
- function - Variable in class boone.map.Function.Scaled
-
- Function.AboutEqual - Class in boone.map
-
About Equal: return 1.0 if (eqValue - range) < value < (eqValue + range).
- Function.AtLeast - Class in boone.map
-
At Least: return 1.0 if value >= minValue, 0.0 else.
- Function.AtMost - Class in boone.map
-
At Most: return 1.0 if value <= maxValue, 0.0 else.
- Function.CatmullRomSpline - Class in boone.map
-
Catmull-Rom Spline Activation Function.
- Function.Clip - Class in boone.map
-
Clip: return value if value in the given range, else the low/high range border value.
- Function.Composition - Class in boone.map
-
composition function, returns g(f(x)).
- Function.Exponential - Class in boone.map
-
The plain exponential function f(x) = e^x with caching.
- Function.GreaterThan - Class in boone.map
-
Greater Than (strict): return 1.0 if value > minValue, 0.0 else.
- Function.Identity - Class in boone.map
-
identity function - maps input to output
- Function.LessThan - Class in boone.map
-
Less Than (strict): return 1.0 if value < maxValue, 0.0 else.
- Function.NaturalSpline - Class in boone.map
-
Natural Cubic Spline Activation Function
- Function.NotImplemented - Exception in boone.map
-
Runtime exception to throw for something that is not implemented.
- Function.ReLU - Class in boone.map
-
The rectified linear unit (ReLU) function f(x) = max(0, x) with first derivative.
- Function.Scaled - Class in boone.map
-
function adding scaling factors,
applied to the function result value (outside).
- Function.Sigmoid - Class in boone.map
-
The sigmoid function f(x) = 1 / (1 + e^(-x)) with first and second derivative.
- Function.Signum - Class in boone.map
-
Signum: 1 if > 0, -1 if < 0, 0 if = 0
- Function.SignumWithoutZero - Class in boone.map
-
Signum Without Zero: 1 if > 0, -1 else
- Function.Sinus - Class in boone.map
-
Sinus: sin(factor * x)
Default: factor = 0.1
First and Second Derivatives are implemented.
- Function.SoftMax - Class in boone.map
-
The softmax function mapping an array of values to a probability distribution by f(xi) = e^(xi) / sumi(e^(xi)).
- Function.Spline - Interface in boone.map
-
Spline function interface.
- Function.TanH - Class in boone.map
-
The tanh function f(x) = (e^x - e^-x) / (e^x + e^-x) with caching and fast, numerically safe computation.
- g - Variable in class boone.map.Function.Composition
-
- GENERATED_AT - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- getAbsDur() - Method in class boone.spike.Spike
-
Returns the absolute refractory period.
- getAccu() - Method in class boone.BrainPart
-
Returns accu value.
- getAccu() - Method in class boone.links.MultiLink
-
Returns the accu of the base link.
- getActivationFn() - Method in class boone.BrainPart
-
Return the current activation function.
- getBaseLink() - Method in class boone.links.MultiLink
-
Returns the base link of this multi link.
- getBasicName(Class) - Static method in class boone.util.ClassHelper
-
Extract the basic class name from a Class object.
- getBatchSize() - Method in class boone.Trainer
-
Returns the (mini)batch size.
- getBeta1() - Method in class boone.training.AdamTrainer
-
Returns the value of beta1 used for the previous mean gradient.
- getBeta2() - Method in class boone.training.AdamTrainer
-
Returns the value of beta2 used for the second moment of the gradient.
- getBias() - Method in class boone.Neuron
-
Returns the bias value.
- getChildOf(Element, String) - Static method in class boone.util.Xml
-
Returns the child of an element and creates the child, if it does not exist.
- getClassPath() - Static method in class boone.Boone
-
Returns the class path used by Boone for class look-up.
- getClassPath() - Static method in class boone.util.ClassHelper
-
Returns the class path.
- getColumnMean(Matrix) - Static method in class boone.util.JamaHelper
-
Calculate mean of column vectors.
- getColumnVector(Matrix, int) - Static method in class boone.util.JamaHelper
-
Returns the column vector of given index.
- getData() - Method in class boone.map.Function.CatmullRomSpline
-
Return the spline coefficient data array.
- getData() - Method in class boone.map.Function.NaturalSpline
-
Return the spline coefficient data array.
- getData() - Method in interface boone.map.Function.Spline
-
- getDefaultHandler() - Static method in class boone.util.ExceptionHandler
-
Return the default exception handler.
- getDelay() - Method in class boone.spike.SpikingLink
-
Return the link delay.
- getDepth() - Method in class boone.structure.Layer
-
Returns the depth of the layer, i.e., the number of maps/channels/filters.
- getDepth() - Method in class boone.structure.Map
-
Returns the depth of this map.
- getDestination() - Method in class boone.spike.SpikeEvent
-
- getDualProperty(Element, String, String, int) - Static method in class boone.util.Xml
-
Returns a property which may have two different names.
- getDualProperty(Element, String, String, long) - Static method in class boone.util.Xml
-
Returns a property which may have two different names.
- getDualProperty(Element, String, String, double) - Static method in class boone.util.Xml
-
Returns a property which may have two different names.
- getDualProperty(Element, String, String, boolean) - Static method in class boone.util.Xml
-
Returns a property which may have two different names.
- getDuration(double) - Static method in class boone.util.Common
-
Returns the time passed since the given time stamp.
- getEpochs() - Method in class boone.Trainer
-
Returns the number of epochs to be trained.
- getEpsilon() - Method in class boone.training.AdamTrainer
-
Returns the fuzz factor used to avoid numerical problems.
- getEpsilon() - Method in class boone.training.RMSpropTrainer
-
Returns the fuzz factor used to avoid numerical problems.
- getErrorSignal() - Method in class boone.Neuron
-
Returns the current error signal.
- getExcludedNames() - Static method in class boone.Boone
-
Returns the strings that cause exclusion of a path to be searched for Boone classes.
- getExternalInput() - Method in class boone.Neuron
-
- getField(Object, String) - Static method in class boone.util.ClassHelper
-
Use Java Reflection to get the value of the object attribute for this Parameter.
- getField(Object, String, Object) - Static method in class boone.util.ClassHelper
-
Use Java Reflection to get the value of the object attribute for this Parameter.
- getFile() - Method in class boone.io.IOFilter
-
Returns the IO file.
- getFilter() - Method in class boone.NeuralNet
-
Returns the IO filter.
- getFilter() - Method in class boone.PatternSet
-
Returns the IO filter.
- getFilterHeight() - Method in class boone.structure.FilterMap
-
Returns the filter height.
- getFilterLink(Neuron, Link) - Method in class boone.structure.FilterMap
-
Returns a cloned filter link.
- getFilters() - Method in class boone.structure.FilterMap
-
Returns the filter bank.
- getFilterWidth() - Method in class boone.structure.FilterMap
-
Returns the filter width.
- getFullName(String) - Static method in class boone.Boone
-
Return the qualified name of a class given the unqualified class name using the internal registry.
- getFunction() - Method in class boone.spike.SpikeEvent
-
- getGamma() - Method in class boone.training.RMSpropTrainer
-
Returns the value of the weight of the current squared gradient.
- getGradient() - Method in class boone.BrainPart
-
Returns gradient information.
- getGradient() - Method in class boone.links.MultiLink
-
Returns the gradient of the base link.
- getHeight() - Method in class boone.structure.Layer
-
Returns the height of the first map (channel 0).
- getHeight() - Method in class boone.structure.Map
-
Returns the height of this map.
- getHiddenLayerOutput(List<Double>) - Method in class boone.training.SAETrainer
-
- getHiddenNeuronCount() - Method in class boone.NeuralNet
-
Return the number of hidden neurons, that is, neurons which are neither input
nor output neurons.
- getHiddenNeuronCount() - Method in class boone.structure.CompiledNeuralNet
-
Returns the number of hidden neurons, that is, neurons which are neither
input nor output neurons.
- getHorizon() - Method in class boone.spike.SpikeEventQueue
-
Return the horizon of this queue.
- getID() - Method in class boone.BrainPart
-
Returns the ID.
- getInput() - Method in class boone.Neuron
-
- getInput(int) - Method in class boone.PatternSet
-
Returns the input feature values of the given feature for all patterns.
- getInputLink(int) - Method in class boone.Neuron
-
Returns the input link of given index.
- getInputLinkCount() - Method in class boone.Neuron
-
Returns the number of input links.
- getInputNeuron(int) - Method in class boone.NeuralNet
-
- getInputNeuronCount() - Method in class boone.NeuralNet
-
Returns the number of input neurons.
- getInputNeuronCount() - Method in class boone.structure.CompiledNeuralNet
-
- getInputPatternSize() - Method in class boone.PatternSet
-
Return the number of values for each input pattern.
- getInputs() - Method in class boone.PatternSet
-
Get the list that holds the network input-related data.
- getInputSpikes(Neuron) - Method in class boone.spike.SpikeSet
-
Get the input of the specified input neuron.
- getLastGradient() - Method in class boone.BrainPart
-
Returns the last gradient information.
- getLastGradient() - Method in class boone.links.MultiLink
-
Returns the last gradient of the base link.
- getLatestSpikeTime() - Method in class boone.spike.SpikingNeuralNet
-
Returns the latest spike time of the spikes currently in the buffer.
- getLatestTime() - Method in class boone.spike.SpikeEventBuffer
-
Returns the latest spike time of all spikes in the buffer.
- getLayer() - Method in class boone.Neuron
-
Returns the layer number of the neuron.
- getLearnRate() - Method in class boone.Trainer
-
Returns the learning rate of the trainer.
- getLevel() - Method in class boone.structure.Layer
-
Returns the level of the layer.
- getLink(int) - Method in class boone.NeuralNet
-
Returns a specific link in the net.
- getLink(int) - Method in class boone.Neuron
-
get a link
- getLinkCount() - Method in class boone.NeuralNet
-
- getLinkCount() - Method in class boone.Neuron
-
Returns the number of links of this neuron.
- getLinkCount() - Method in class boone.structure.CompiledNeuralNet
-
- getLinkCount() - Method in class boone.structure.Layer
-
Returns the the number of links into this layer.
- getLinkCount() - Method in class boone.structure.Map
-
Returns the the number of links into this map.
- getLinkID(long) - Method in class boone.NeuralNet
-
Returns the link with the given ID.
- getLinkInput() - Method in class boone.Neuron
-
Return the value of the linkInput; please see above.
- getLinks() - Method in class boone.Neuron
-
Get all the input and output links.
- getLinkTo(Neuron) - Method in class boone.Neuron
-
Returns the link connecting this neuron to the given other neuron, which may also be the same neuron.
- getLowerLeft(int) - Method in class boone.map.HexagonTopology
-
Returns the lower left neighbor neuron, if there.
- getLowerRight(int) - Method in class boone.map.HexagonTopology
-
Returns the lower right neighbor neuron, if there.
- getMapCount() - Method in class boone.structure.Layer
-
Returns the number of maps in this layer.
- getMaps() - Method in class boone.structure.Layer
-
Returns the maps of this layer.
- getMaxCycles() - Method in class boone.NeuralNet
-
- getMaxIndex(double[]) - Static method in class boone.util.Common
-
Returns the index of the max value of an array.
- getMaxIndex(List<Double>) - Static method in class boone.util.Common
-
Returns the index of the max value of a Double list.
- getMaxIndex(List<List<Double>>, int) - Static method in class boone.util.Patterns
-
Returns the index of the maximal value in a pattern.
- getMaxUpdateValue() - Method in class boone.training.RpropTrainer
-
- getMaxValue() - Method in class boone.map.Function.AboutEqual
-
- getMaxValue() - Method in class boone.map.Function.AtLeast
-
- getMaxValue() - Method in class boone.map.Function.AtMost
-
- getMaxValue() - Method in class boone.map.Function.CatmullRomSpline
-
Return Double.MAX_VALUE; no maximum estimation is done.
- getMaxValue() - Method in class boone.map.Function.Clip
-
- getMaxValue() - Method in class boone.map.Function.Composition
-
Returns the maximum value of the g function.
- getMaxValue() - Method in class boone.map.Function.Exponential
-
- getMaxValue() - Method in class boone.map.Function
-
Return the largest possible function value.
- getMaxValue() - Method in class boone.map.Function.GreaterThan
-
- getMaxValue() - Method in class boone.map.Function.Identity
-
- getMaxValue() - Method in class boone.map.Function.LessThan
-
- getMaxValue() - Method in class boone.map.Function.NaturalSpline
-
Return Double.MAX_VALUE; no minimum estimation is implemented.
- getMaxValue() - Method in class boone.map.Function.ReLU
-
- getMaxValue() - Method in class boone.map.Function.Scaled
-
- getMaxValue() - Method in class boone.map.Function.Sigmoid
-
- getMaxValue() - Method in class boone.map.Function.Signum
-
- getMaxValue() - Method in class boone.map.Function.SignumWithoutZero
-
- getMaxValue() - Method in class boone.map.Function.Sinus
-
- getMaxValue() - Method in class boone.map.Function.SoftMax
-
- getMaxValue() - Method in class boone.map.Function.TanH
-
- getMaxValue() - Method in class boone.spike.NeuronPotential
-
- getMaxValue() - Method in class boone.spike.PostsynapticPotential
-
- getMaxValue() - Method in class boone.spike.Spike
-
Return the duration of the absolute refractoriness phase.
- getMinUpdateValue() - Method in class boone.training.RpropTrainer
-
- getMinValue() - Method in class boone.map.Function.AboutEqual
-
- getMinValue() - Method in class boone.map.Function.AtLeast
-
- getMinValue() - Method in class boone.map.Function.AtMost
-
- getMinValue() - Method in class boone.map.Function.CatmullRomSpline
-
Return -Double.MAX_VALUE; no minimum estimation is implemented.
- getMinValue() - Method in class boone.map.Function.Clip
-
- getMinValue() - Method in class boone.map.Function.Composition
-
Returns the minimum value of the g function.
- getMinValue() - Method in class boone.map.Function.Exponential
-
- getMinValue() - Method in class boone.map.Function
-
Return the smallest possible function value.
- getMinValue() - Method in class boone.map.Function.GreaterThan
-
- getMinValue() - Method in class boone.map.Function.Identity
-
- getMinValue() - Method in class boone.map.Function.LessThan
-
- getMinValue() - Method in class boone.map.Function.NaturalSpline
-
Return -Double.MAX_VALUE; no minimum estimation is implemented.
- getMinValue() - Method in class boone.map.Function.ReLU
-
- getMinValue() - Method in class boone.map.Function.Scaled
-
- getMinValue() - Method in class boone.map.Function.Sigmoid
-
- getMinValue() - Method in class boone.map.Function.Signum
-
- getMinValue() - Method in class boone.map.Function.SignumWithoutZero
-
- getMinValue() - Method in class boone.map.Function.Sinus
-
- getMinValue() - Method in class boone.map.Function.SoftMax
-
- getMinValue() - Method in class boone.map.Function.TanH
-
- getMinValue() - Method in class boone.spike.NeuronPotential
-
- getMinValue() - Method in class boone.spike.PostsynapticPotential
-
- getMinValue() - Method in class boone.spike.Spike
-
- getName() - Method in class boone.BrainPart
-
Return the name of this BrainPart.
- getName() - Method in class boone.links.MultiLink
-
Returns the name of the base link.
- getNameFromClassPath(String) - Static method in class boone.util.ClassHelper
-
Returns a path containing 'name' in the resources of the class path.
- getNameFromDir(File, String) - Static method in class boone.util.ClassHelper
-
Returns the path to a file name containing 'name' starting recursively at directory 'file'.
- getNameFromFileSystem(String, String) - Static method in class boone.util.ClassHelper
-
Returns a path containing 'name', where the search starts at 'path'.
- getNameFromJar(File, String) - Static method in class boone.util.ClassHelper
-
Returns a jar file entry containing a resource with 'name'.
- getNames() - Method in class boone.PatternSet
-
Returns the pattern names.
- getNeighbors(Neuron, int) - Method in class boone.map.Topology
-
Returns all neighbors within a given 'radius' of the given neuron.
- getNet(int) - Method in class boone.Brain
-
Return a network.
- getNet() - Method in class boone.map.Topology
-
Returns the associated net.
- getNetCount() - Method in class boone.Brain
-
Return the number of neural networks.
- getNetwork() - Method in class boone.Trainer
-
Returns the network associated with this trainer.
- getNeuron(int) - Method in class boone.NeuralNet
-
- getNeuron(int, int, int) - Method in class boone.structure.Layer
-
Returns the neuron with given coordinates.
- getNeuron(int) - Method in class boone.structure.Map
-
Returns the neuron with given index.
- getNeuron(int, int) - Method in class boone.structure.Map
-
Returns the neuron with given coordinates.
- getNeuronCount() - Method in class boone.NeuralNet
-
Returns the number of neurons in this net.
- getNeuronCount() - Method in class boone.structure.CompiledNeuralNet
-
- getNeuronID(long) - Method in class boone.NeuralNet
-
Returns the neuron with the given ID.
- getNeuronIndex(Neuron) - Method in class boone.NeuralNet
-
- getNeurons() - Method in class boone.map.HexagonTopology
-
Returns the dimensions of the map.
- getNeurons() - Method in class boone.map.Topology
-
Returns the dimensions of the map.
- getNeurons() - Method in class boone.structure.Layer
-
Returns the neurons in this layer.
- getNeurons() - Method in class boone.structure.Map
-
Returns the neurons in this map.
- getNeuronsOfLayer(int) - Method in class boone.training.SAETrainer
-
Extract all neurons that are part of same layer
- getNextElement() - Method in class boone.PatternSet
-
Returns the index of the next pattern.
- getNextSet(NeuralNet, PatternSet) - Method in class boone.training.SAETrainer
-
Generate the next pattern set from current pattern set by extracting hidden layer activation.
- getNextToken(boolean) - Method in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
Reads the next token from the input source.
- getNextToken() - Method in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- getNodeContent(Element, String) - Static method in class boone.util.Xml
-
Returns the content of either a child or a attribute of node parent
- getOrigin() - Method in class boone.spike.SpikeEvent
-
- getOtherNeuron(Neuron) - Method in class boone.Link
-
Get the other neuron of the link.
- getOutput(double[]) - Method in class boone.NeuralNet
-
Extract the output pattern from the network.
- getOutput() - Method in class boone.Neuron
-
Returns the current output value of this neuron.
- getOutput(int) - Method in class boone.PatternSet
-
Returns the output values of the given output for all patterns.
- getOutput() - Method in class boone.structure.CompiledNeuralNet
-
- getOutput(double[]) - Method in class boone.structure.NetCompiler.BooneCompiledNet
-
Extract the output pattern from the network.
- getOutput(double[]) - Method in interface boone.structure.NetCompiler.CompiledNet
-
Extract the output pattern from the network.
- getOutputLink(int) - Method in class boone.Neuron
-
Returns the output link of given index.
- getOutputLinkCount() - Method in class boone.Neuron
-
Returns the number of output links.
- getOutputNeuron(int) - Method in class boone.NeuralNet
-
Returns a specific output neuron in the network.
- getOutputNeuronCount() - Method in class boone.NeuralNet
-
- getOutputNeuronCount() - Method in class boone.structure.CompiledNeuralNet
-
- getOutputNeuronIndex(Neuron) - Method in class boone.NeuralNet
-
Returns the index of the given output neuron in the internal list.
- getOutputPatternSize() - Method in class boone.PatternSet
-
Return the number of values for each output pattern.
- getOutputs() - Method in class boone.PatternSet
-
Get the list that holds the network output-related data.
- getOutputSpikes(Neuron) - Method in class boone.spike.SpikeSet
-
Get the output of the specified output neuron.
- getPadHeight() - Method in class boone.structure.FilterMap
-
Returns the pad height.
- getPadWidth() - Method in class boone.structure.FilterMap
-
Returns the pad width.
- getPosition() - Method in class boone.Neuron
-
Returns the position of the neuron.
- getPreviousHead() - Method in class boone.spike.SpikeEventBuffer
-
Return the element removed as a result of the most recent
call to poll(), remove() or take(),
or return null if no such element exists.
- getProperties() - Method in class boone.PatternSet
-
Get the properties to be stored along with this data set.
- getProperty(Element, String, String) - Static method in class boone.util.Xml
-
Returns the content of either a child node or an attribute of the XML
element.
- getProperty(Element, String, int) - Static method in class boone.util.Xml
-
Returns the content of either a child node or an attribute of the XML element.
- getProperty(Element, String, long) - Static method in class boone.util.Xml
-
Returns the content of either a child node or an attribute of the XML element.
- getProperty(Element, String, double) - Static method in class boone.util.Xml
-
Returns the content of either a child node or an attribute of the XML
element.
- getProperty(Element, String, float) - Static method in class boone.util.Xml
-
Returns the content of either a child node or an attribute of the XML
element.
- getProperty(Element, String, boolean) - Static method in class boone.util.Xml
-
Returns the content of either a child node or an attribute of the XML element.
- getQualifiedName(String) - Static method in class boone.util.ClassHelper
-
Returns the qualified name of a possibly unqualified class name.
- getRandom() - Static method in class boone.util.Common
-
Returns the common random number generator.
- getRandom(double, double) - Static method in class boone.util.Common
-
Returns a random value from the interval [low, high).
- getRank(List<Double>, int) - Method in class boone.Trainer
-
Returns the ranked activation of the given output neuron and the given input pattern.
- getRateDecFactor() - Method in class boone.training.RpropTrainer
-
- getRateIncFactor() - Method in class boone.training.RpropTrainer
-
- getReadException() - Method in class boone.util.StreamParser
-
return the last read exception and clear it.
- getRelDur() - Method in class boone.spike.Spike
-
Returns the relative refractory period.
- getRight(int) - Method in class boone.map.HexagonTopology
-
Returns the right neighbor neuron, if there.
- getRowMean(Matrix) - Static method in class boone.util.JamaHelper
-
Calculate mean of row vectors.
- getRowVector(Matrix, int) - Static method in class boone.util.JamaHelper
-
Returns the row vector of given index.
- getSeparatorChar(String) - Static method in class boone.util.Common
-
Determines the separator character in a given string.
- getSet(int) - Method in class boone.Brain
-
Return a data set.
- getSetCount() - Method in class boone.Brain
-
Return the number of data sets.
- getSink() - Method in class boone.Link
-
Returns the sink neuron.
- getSize() - Method in class boone.structure.Layer
-
Returns the size of this layer, i.e., the number of neurons.
- getSize() - Method in class boone.structure.Map
-
Returns the size of this map, i.e., the number of neurons.
- getSizes() - Method in class boone.map.HexagonTopology
-
Returns the size (length) of each dimension of the map.
- getSizes() - Method in class boone.map.Topology
-
Returns the size (length) of each dimension of the map.
- getSource() - Method in class boone.Link
-
Returns the source neuron.
- getStartRadius() - Method in class boone.training.SOMTrainer
-
- getStorable(Element, String) - Static method in class boone.util.Xml
-
Creates a storable from the child with given name of the given element.
- getStorable(Element) - Static method in class boone.util.Xml
-
Creates a storable from the given element.
- getStreamSize() - Method in class boone.io.IOFilter
-
Returns the number of patterns read in a single stream event.
- getStrideHeight() - Method in class boone.structure.FilterMap
-
Returns the stride height.
- getStrideWidth() - Method in class boone.structure.FilterMap
-
Returns the stride width.
- getSubSet(PatternSet, int, int) - Static method in class boone.util.Patterns
-
Returns a subset of the given pattern set.
- getTarget(int) - Method in class boone.PatternSet
-
Returns the target values of the given target for all patterns.
- getTargetLabel(int) - Method in class boone.PatternSet
-
Returns the name of the given target value.
- getTargetLabelCount() - Method in class boone.PatternSet
-
Returns the number of targets with a name.
- getTargetLabelOfPattern(int) - Method in class boone.PatternSet
-
Returns the target label of the given pattern.
- getTargetPatternSize() - Method in class boone.PatternSet
-
Return the number of values for each target pattern.
- getTargets() - Method in class boone.PatternSet
-
Get the list that holds the network training-related data.
- getTargetSpikes(Neuron) - Method in class boone.spike.SpikeSet
-
Get the target values of the specified output neuron.
- getTestData() - Method in class boone.Trainer
-
Returns the programs data set.
- getThreshold() - Method in class boone.spike.SpikingNeuron
-
Returns the firing threshold.
- getTime() - Method in class boone.spike.SpikeEvent
-
- getTimeStamp() - Static method in class boone.util.Common
-
Returns the current time stamp in milli-seconds.
- getTopology() - Method in class boone.NeuralNet
-
Returns the topology of the net.
- getTopology() - Method in class boone.training.SOMTrainer
-
Returns the topology of the SOM to be trained.
- getTotalNeurons() - Method in class boone.map.HexagonTopology
-
Returns the total number of map neurons.
- getTotalNeurons() - Method in class boone.map.Topology
-
Returns the total number of map neurons.
- getTrainer() - Method in class boone.NeuralNet
-
Returns the trainer of the net.
- getTrainingData() - Method in class boone.Trainer
-
Returns the training data set.
- getTrainingSignalGenerator() - Method in class boone.Trainer
-
Returns the current training signal generator for this trainer.
- getType() - Method in class boone.spike.SpikeEvent
-
The type signals, if this event represents an emitted or received spike.
- getUniqueID() - Static method in class boone.BrainPart
-
Returns a unique ID for a brain part.
- getValue() - Method in class boone.Link
-
- getWeight() - Method in class boone.BrainPart
-
Returns the weight of this link.
- getWeight() - Method in class boone.links.MultiLink
-
Returns the weight of the base link.
- getWidth() - Method in class boone.structure.Layer
-
Returns the width of the first map (channel 0).
- getWidth() - Method in class boone.structure.Map
-
Returns the width of this map.
- getWinningNeuron(List<Double>) - Method in class boone.Trainer
-
Returns the output neuron with largest activation upon presentation of 'input'.
- getXPos() - Method in class boone.map.Position
-
- getYPos() - Method in class boone.map.Position
-
- getZeroInputAfterFirstCycle() - Method in class boone.NeuralNet
-
Return whether the NeuralNet zeroes out the external input of the input neurons
after the first evaluation cycle.
- getZPos() - Method in class boone.map.Position
-
- GreaterThan() - Constructor for class boone.map.Function.GreaterThan
-
- GreaterThan(double) - Constructor for class boone.map.Function.GreaterThan
-
- gridWidth - Variable in class boone.io.SNNSNetFilter
-
Neuron position translation - Grid width (scale)
- radius - Variable in class boone.training.SOMTrainer
-
The current neighborhood radius.
- random - Static variable in class boone.util.Common
-
The common RNG.
- randomize() - Method in class boone.BrainPart
-
Randomizes the weight/bias value within [-0.1, 0.1).
- randomize(double, double) - Method in class boone.BrainPart
-
Randomizes the weight/bias value within the given bounds.
- randomize() - Method in class boone.links.MultiLink
-
Sets the base link weight to a random value.
- randomize(double, double) - Method in class boone.links.MultiLink
-
Sets the base link weight to a random value in [min, max).
- randomize() - Method in class boone.NeuralNet
-
Randomizes the network parameters to some meaningful values.
- randomize() - Method in class boone.spike.SpikingLink
-
Sets the weight to 1.0 and the link delay to a random double value in the interval [0, 5).
- randomize(double, double) - Method in class boone.spike.SpikingLink
-
Sets the weight to 1.0 and the link delay to a random double value
in the (checked) interval [min, max).
- randomize() - Method in class boone.spike.SpikingNeuron
-
Calls super.randomize() and randomizes the threshold value within [0.0, 30.0).
- randomize(double, double) - Method in class boone.spike.SpikingNeuron
-
Calls super.randomize(double, double) and randomizes the threshold value within the given bounds.
- rateDecFactor - Variable in class boone.training.RpropTrainer
-
The negative update value change (default 0.5).
- rateIncFactor - Variable in class boone.training.RpropTrainer
-
The positive update value change (default 1.2).
- readException - Variable in class boone.util.StreamParser
-
the last exception while reading
- readFloatNumber() - Method in class boone.util.StreamParser
-
Parse a floating-point number.
- readIntNumber() - Method in class boone.util.StreamParser
-
Parse an integer number.
- readLine() - Method in class boone.util.StreamParser
-
Read until the end of the line.
- readSpace() - Method in class boone.util.StreamParser
-
Everything <= 32 is considered whitespace.
- readSpaceOnly() - Method in class boone.util.StreamParser
-
Everything <= 32 is considered whitespace; this method reads over it.
- readState - Variable in class boone.util.StreamParser
-
the current read state.
- readUntil(char) - Method in class boone.util.StreamParser
-
read until the given character occurs.
- readUntilCharOrNewline(char) - Method in class boone.util.StreamParser
-
Read until the given character occurs, or until a Newline (LF, '\n') occurs.
- readValues(StreamParser, int, char, List<Double>) - Method in class boone.io.CSVPatternFilter
-
Reads maximally 'count' double values from a pattern file.
- readValues(StreamParser, int, char, List<Double>) - Method in class boone.io.IOFilter
-
Reads 'count' double values from a pattern file.
- readWord() - Method in class boone.util.StreamParser
-
Read a word, until the next whitespace.
- record(SpikeSet, double, double) - Method in class boone.spike.SpikingNeuron
-
Start recording the timestamps of spikes fired by this neuron to the specified SpikeSet;
Ignore any timestamps outside the specified time interval.
- recordStart(SpikeSet) - Method in class boone.spike.SpikingNeuron
-
Start recording the timestamps of spikes fired by this neuron to the specified SpikeSet.
- recordStop() - Method in class boone.spike.SpikingNeuron
-
Stop recording the timestamps of spikes fired by this neuron.
- RECURRENT - Static variable in class boone.NeuralNet
-
A recurrent network.
- ReLU() - Constructor for class boone.map.Function.ReLU
-
- removeDanglingLinks(NeuralNet) - Static method in class boone.util.Nets
-
Removes safely all dangling links of a network.
- removeDanglingNeurons(NeuralNet) - Static method in class boone.util.Nets
-
Removes safely all dangling hidden neurons of a network.
- removeLink(Link) - Method in class boone.NeuralNet
-
remove a link from our network.
- removeLink(Link) - Method in class boone.spike.SpikingNeuralNet
-
- removeMap(int) - Method in class boone.structure.Layer
-
Removes the map with given index from this layer.
- removeNet(int) - Method in class boone.Brain
-
Remove a network from the brain.
- removeNet(NeuralNet) - Method in class boone.Brain
-
Remove a network from the brain.
- removeNeuron(Neuron) - Method in class boone.NeuralNet
-
Removes a neuron and updates the associated links, but no link lists.
- removeNeuron(Neuron) - Method in class boone.spike.SpikingNeuralNet
-
- removeSet(int) - Method in class boone.Brain
-
Remove a data set from the brain.
- removeSet(PatternSet) - Method in class boone.Brain
-
Remove a data set from the brain.
- replace(List<E>, E, E) - Static method in class boone.util.Common
-
Replaces element a with element b in the list.
- replaceFrom(Link) - Method in class boone.Link
-
Replaces the given old link with this new link, i.e.
- replaceFrom(Link) - Method in class boone.spike.SpikingLink
-
- replaceLink(Link, Link) - Method in class boone.NeuralNet
-
replace a link with another.
- replaceLink(Link, Link) - Method in class boone.spike.SpikingNeuralNet
-
- replaceNeuron(Neuron, Neuron) - Method in class boone.Link
-
Replace the given old neuron with a new neuron.
- replaceNeuron(Neuron, Neuron) - Method in class boone.NeuralNet
-
Replace a neuron with another.
- replaceNeuron(Neuron, Neuron) - Method in class boone.spike.SpikingNeuralNet
-
- reset() - Method in class boone.BrainPart
-
Resets internal attributes.
- reset() - Method in class boone.io.BooneFilter
-
Resets the filter to an initial state.
- reset() - Method in class boone.io.CSVPatternFilter
-
Resets the filter to an initial state.
- reset() - Method in class boone.io.IOFilter
-
Resets the filter to an initial state.
- reset() - Method in class boone.links.MultiLink
-
Resets this link and the base link.
- reset() - Method in class boone.Neuron
-
Resets internal neuron attributes.
- reset() - Method in class boone.spike.SpikingNeuron
-
Clears the spike history of this SpikingNeuron.
- reset() - Method in class boone.structure.Map
-
Resets the internal state of this map (does nothing here).
- reset() - Method in class boone.Trainer
-
Resets the trainer to initial values in order to start a new training procedure.
- reset() - Method in class boone.training.AdamTrainer
-
Resets bias correction for a fresh training procedure.
- reset() - Method in class boone.training.BackpropTrainer
-
Resets all neurons and links of the net for a fresh training procedure.
- reset() - Method in class boone.training.HebbTrainer
-
Does nothing.
- reset() - Method in class boone.training.HopfieldDeltaTrainer
-
Does nothing.
- reset() - Method in class boone.training.LVQTrainer
-
Resets the trainer by setting the output neuron's error signal to 'learnRate'.
- reset() - Method in class boone.training.RpropTrainer
-
Resets all neurons and links of the net for a fresh training procedure.
- reset() - Method in class boone.training.SAETrainer
-
- reset() - Method in class boone.training.SOMTrainer
-
Resets the neighborhood radius to the initial one, and sets the linear radius change such that
after all epochs the radius is 1.0.
- resetLayer(int) - Method in class boone.training.SAETrainer
-
Reset STRUCTURE of net (activation function, bias, input or output...)
by resetting of neurons in part net AFTER training
- resetTrainer() - Method in class boone.training.SAETrainer
-
Trainer gets new part net to train
- resume() - Method in class boone.spike.SpikingNeuralNet
-
Resume scheduling and propagating spikes.
- RMSpropTrainer - Class in boone.training
-
The Root Mean Square propagation trainer.
- RMSpropTrainer() - Constructor for class boone.training.RMSpropTrainer
-
Creates an RMSprop trainer with a learn rate of 0.001, a batch size of 32.
- RootSolver - Class in boone.util
-
This class contains methods to find roots and limits of functions.
- RootSolver() - Constructor for class boone.util.RootSolver
-
- RpropTrainer - Class in boone.training
-
The Resilient Back-propagation trainer.
- RpropTrainer() - Constructor for class boone.training.RpropTrainer
-
Creates an Rprop trainer with a learn rate (initial update value) of 0.1.
- SAETrainer - Class in boone.training
-
The SAE trainer can transform a regular feed-forward network into a stacked auto-encoder.
- SAETrainer() - Constructor for class boone.training.SAETrainer
-
- SAETrainer(Trainer, int) - Constructor for class boone.training.SAETrainer
-
Create a new SAE trainer using a
SquareError, a given trainer and a given number of steps
- save(File) - Method in class boone.Brain
-
Save a Brain.
- save(Storable) - Method in class boone.io.BooneFilter
-
Saves Boone data to an XML file.
- save(Storable) - Method in class boone.io.CSVPatternFilter
-
Saves a pattern set to a CSV file.
- save(Storable) - Method in class boone.io.IOFilter
-
Saves Boone data to a file.
- save(Storable) - Method in class boone.io.Proben1PatternFilter
-
Saves a pattern set to a Proben1 file.
- save(Storable) - Method in class boone.io.SNNSNetFilter
-
Writes a network to a file in SNNS format.
- save(Storable) - Method in class boone.io.SNNSPatternFilter
-
Saves the given pattern set to a file in SNNS format.
- save(File) - Method in class boone.NeuralNet
-
Save a NeuralNet to the given file, in the Boone XNet format, using the IOFilter class.
- save(File) - Method in class boone.PatternSet
-
Save the data set to the given file.
- save(IOFilter) - Method in class boone.PatternSet
-
Saves the pattern set to the given filter.
- saveDocument(Document, OutputStream) - Static method in class boone.util.Xml
-
Writes a JDOM document to the given output stream.
- Scaled() - Constructor for class boone.map.Function.Scaled
-
- Scaled(double, double, Function) - Constructor for class boone.map.Function.Scaled
-
- scientific - Static variable in class boone.util.Common
-
For numbers in a power format.
- searchDanglingLink(List<Link>, long) - Static method in class boone.util.Nets
-
Searches a dangling link of given ID in a list.
- searchLink(List<Link>, long) - Static method in class boone.util.Nets
-
Searches the link of given ID in a list.
- searchNeighbors(int, int) - Method in class boone.map.HexagonTopology
-
Searches direct hexagonal neighbors of the given center neuron.
- searchNeighbors(int, int) - Method in class boone.map.Topology
-
Sets the map at the given neuron index to value.
- searchNeuron(List<Neuron>, long) - Static method in class boone.util.Nets
-
Searches the neuron of given ID in a list.
- sections(NeuralNet) - Method in class boone.io.SNNSNetFilter.ENSNNSParser
-
sections ::= COMMENT unit_section [COMMENT default_section]
[COMMENT site_section] [COMMENT type_section]
[COMMENT subnet_section] [COMMENT conn_section]
[COMMENT layer_section] [COMMENT trans_section]
[COMMENT time_delay_section] COMMENT
- set(float, float) - Method in class boone.map.Position
-
Set new position in 2D.
- set(float, float, float) - Method in class boone.map.Position
-
Set new position in 3D.
- set(Position) - Method in class boone.map.Position
-
Set new position in 3D, copying from another Position.
- set(float[]) - Method in class boone.map.Position
-
Set from a float array.
- setAbsDur(double) - Method in class boone.spike.Spike
-
Sets the absolute refractory period.
- setAccu(double) - Method in class boone.BrainPart
-
Sets accu value.
- setAccu(double) - Method in class boone.links.MultiLink
-
Sets the accu of the base link.
- setActivationFn(Function) - Method in class boone.BrainPart
-
Set the brain part's activation function.
- setActivationFn(Function) - Method in class boone.spike.SpikingNeuron
-
Set the function that is used to describe the form of the spikes fired by this neuron.
- setBatchSize(int) - Method in class boone.Trainer
-
Sets the (mini)batch size.
- setBeta1(double) - Method in class boone.training.AdamTrainer
-
Sets the value of the weight of the current gradient.
- setBeta2(double) - Method in class boone.training.AdamTrainer
-
Sets the value of the weight of the second moment of the gradient.
- setBias(double) - Method in class boone.Neuron
-
Sets the bias value.
- setBuffer(SpikeEventBuffer) - Method in class boone.spike.SpikingLink
-
Set a reference to the global buffer that holds all spikes generated inside the
SpikingNeuralNet to which this link belongs.
- setBuffer(SpikeEventBuffer) - Method in class boone.spike.SpikingNeuron
-
Set a reference to the global buffer that holds all spikes generated inside the
SpikingNeuralNet to which this neuron belongs.
- setCompressed(boolean) - Method in class boone.io.IOFilter
-
Sets the file compression flag.
- setData(double[]) - Method in class boone.map.Function.CatmullRomSpline
-
Set the cubic spline coefficients array.
- setData(double[]) - Method in class boone.map.Function.NaturalSpline
-
Set a new spline coefficient data array, and re-calculate the precomputed values.
- setData(double[]) - Method in interface boone.map.Function.Spline
-
- setDefaultHandler(ExceptionHandler) - Static method in class boone.util.ExceptionHandler
-
Set the default exception handler.
- setDelay(double) - Method in class boone.spike.SpikingLink
-
Set the link delay.
- setDestination(BrainPart) - Method in class boone.spike.SpikeEvent
-
- setDirected(boolean) - Method in class boone.Link
-
Sets the direction flag.
- setEpochs(int) - Method in class boone.Trainer
-
Sets the number of epochs.
- setEpsilon(double) - Method in class boone.training.AdamTrainer
-
Returns the fuzz factor used to avoid numerical problems.
- setEpsilon(double) - Method in class boone.training.RMSpropTrainer
-
Returns the fuzz factor used to avoid numerical problems.
- setErrorSignal(double) - Method in class boone.Neuron
-
Sets the error signal.
- setExternalInput(double) - Method in class boone.Neuron
-
Set the neuron's external input, e.g.
- setField(Object, String, Object) - Static method in class boone.util.ClassHelper
-
Set the value of this parameter.
- setFile(File) - Method in class boone.io.IOFilter
-
Sets the IO file.
- setFilter(IOFilter) - Method in class boone.NeuralNet
-
Sets the IO filter.
- setFilter(IOFilter) - Method in class boone.PatternSet
-
Sets the IO filter.
- setFlavor(int) - Method in class boone.training.LVQTrainer
-
- setFullName(String, String) - Static method in class boone.Boone
-
Adds the mapping to the registry.
- setFunction(Function) - Method in class boone.spike.SpikeEvent
-
- setGamma(double) - Method in class boone.training.RMSpropTrainer
-
Sets the value of the weight of the current squared gradient.
- setGradient(double) - Method in class boone.BrainPart
-
Sets gradient information.
- setGradient(double) - Method in class boone.links.MultiLink
-
Sets the gradient of the base link.
- setHorizon(double) - Method in class boone.spike.SpikeEventQueue
-
Set the horizon of this queue.
- setID(long) - Method in class boone.BrainPart
-
Sets the ID.
- setImplicitQuoting(boolean) - Method in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
Set implicit quoting for STRING tokens.
- setInput(double[]) - Method in class boone.NeuralNet
-
Load the input pattern into the network.
- setInput(List<Double>) - Method in class boone.NeuralNet
-
Load the input pattern into the network.
- setInput(double) - Method in class boone.Neuron
-
Sets the current input value of the neuron.
- setInput(SpikeSet) - Method in class boone.spike.SpikingNeuralNet
-
Set the firing times for the input neurons as defined in the specified
SpikeSet.
- setInput(double[]) - Method in class boone.structure.CompiledNeuralNet
-
- setInput(double[]) - Method in class boone.structure.NetCompiler.BooneCompiledNet
-
Load the input pattern into the network.
- setInput(double[]) - Method in interface boone.structure.NetCompiler.CompiledNet
-
Load the input pattern into the network.
- setInputNeuron(boolean) - Method in class boone.Neuron
-
define whether this neuron is an input neuron.
- setInputs(List<List<Double>>) - Method in class boone.PatternSet
-
Sets the network inputs.
- setInputSpikes(Neuron, List<Double>) - Method in class boone.spike.SpikeSet
-
Set the input for the specified input neuron.
- setIOType(boolean, boolean) - Method in class boone.structure.Layer
-
Sets the layer maps' IO status.
- setIOType(boolean, boolean) - Method in class boone.structure.Map
-
Sets the map neurons' IO status.
- setLastGradient(double) - Method in class boone.BrainPart
-
Remembers the last gradient information.
- setLastGradient(double) - Method in class boone.links.MultiLink
-
Remembers the last gradient of the base link.
- setLayer(int) - Method in class boone.Neuron
-
Sets the layer number.
- setLearnRate(double) - Method in class boone.Trainer
-
Set the learn rate for this Trainer.
- setLevel(int) - Method in class boone.structure.Layer
-
Sets the level (number) of the layer.
- setLinkInput(double) - Method in class boone.Neuron
-
Sets the neuron's link input.
- setMapValue(int, int) - Method in class boone.map.HexagonTopology
-
Sets a map value at the spot corresponding to the neuron index.
- setMapValue(int, int) - Method in class boone.map.Topology
-
Sets the map at the given neuron index to value.
- setMaxCycles(int) - Method in class boone.NeuralNet
-
- setMaxUpdateValue(double) - Method in class boone.training.RpropTrainer
-
- setMinUpdateValue(double) - Method in class boone.training.RpropTrainer
-
- setName(String) - Method in class boone.BrainPart
-
Set the name of this BrainPart.
- setNet(NeuralNet) - Method in class boone.map.Topology
-
Sets the associated net.
- setNetwork(NeuralNet) - Method in class boone.Trainer
-
Sets the network for this trainer.
- setNetwork(NeuralNet) - Method in class boone.training.SOMTrainer
-
Sets the network for trainer and topology.
- setOrigin(BrainPart) - Method in class boone.spike.SpikeEvent
-
- setOutput(double) - Method in class boone.Neuron
-
Set the current output value of this neuron.
- setOutputNeuron(boolean) - Method in class boone.Neuron
-
define whether this neuron is an output neuron.
- setOutputSpikes(Neuron, List<Double>) - Method in class boone.spike.SpikeSet
-
Set the output for the specified output neuron.
- setParameters(Object) - Method in class boone.map.Function
-
Set parameters, if needed.
- setParameters(Object) - Method in class boone.map.Function.SoftMax
-
- setPassNewlines(boolean) - Method in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- setPosition(Position) - Method in class boone.Neuron
-
Sets the neuron position.
- setPreviousHead(SpikeEvent) - Method in class boone.spike.SpikeEventBuffer
-
Set the element removed as a result of the most recent
call to poll(), remove() or take().
- setPrint(boolean) - Method in class boone.training.SAETrainer
-
- setProperties(Properties) - Method in class boone.PatternSet
-
Set the properties to be stored along with this data set.
- setRateDecFactor(double) - Method in class boone.training.RpropTrainer
-
- setRateIncFactor(double) - Method in class boone.training.RpropTrainer
-
- setRealTimeMode(boolean) - Method in class boone.spike.SpikingNeuralNet
-
Set whether the network should run in real-time mode.
- setRelDur(double) - Method in class boone.spike.Spike
-
Sets the relative refractory period.
- setShowNames(boolean) - Method in class boone.util.UMatrix
-
Sets, if pattern names are shown.
- setShuffle(boolean) - Method in class boone.Trainer
-
Sets the shuffle flag.
- setSink(Neuron) - Method in class boone.Link
-
Sets the link's sink neuron.
- setSource(Neuron) - Method in class boone.Link
-
Sets the link's source neuron.
- setStartRadius(double) - Method in class boone.training.SOMTrainer
-
- setStepMode(boolean) - Method in class boone.Trainer
-
Sets the step mode.
- setSuppressKeywords(boolean) - Method in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- setTargetLabel(int, String) - Method in class boone.PatternSet
-
Sets the label for the given target value.
- setTargets(List<List<Double>>) - Method in class boone.PatternSet
-
Sets the network targets.
- setTargetSpikes(Neuron, List<Double>) - Method in class boone.spike.SpikeSet
-
Set the target values for the specified output neuron.
- setTestData(PatternSet) - Method in class boone.Trainer
-
Sets the programs data set.
- setThreshold(double) - Method in class boone.spike.SpikingNeuron
-
Sets the firing threshold potential.
- setTime(double) - Method in class boone.spike.SpikeEvent
-
- setTopology(int) - Method in class boone.NeuralNet
-
Sets the topology of the net.
- setTrainable(boolean) - Method in class boone.BrainPart
-
Sets status.
- setTrainer(Trainer) - Method in class boone.NeuralNet
-
Assigns a trainer to the network and prepares the network for training.
- setTrainingData(PatternSet) - Method in class boone.Trainer
-
Sets the training data set.
- setTrainingSignalGenerator(TrainingSignalGenerator) - Method in class boone.Trainer
-
Set the training signal generator for this trainer.
- setType(int) - Method in class boone.spike.SpikeEvent
-
The type signals, if this event represents an emitted or received spike.
- setUsingBias(boolean) - Method in class boone.Neuron
-
- setValue(double) - Method in class boone.Link
-
- setWeight(double) - Method in class boone.BrainPart
-
Sets the weight/bias of this part.
- setWeight(double) - Method in class boone.links.MultiLink
-
Sets the weight of the base link.
- setXPos(float) - Method in class boone.map.Position
-
- setYPos(float) - Method in class boone.map.Position
-
- setZeroInputAfterFirstCycle(boolean) - Method in class boone.NeuralNet
-
Define whether to reset the external input of the input neurons to zero
after the first cycle when innervating the network.
- setZPos(float) - Method in class boone.map.Position
-
- shuffle() - Method in class boone.PatternSet
-
Reorders the patterns in this set randomly.
- shuffle - Variable in class boone.Trainer
-
Indicates random shuffling of training data.
- shuffle(PatternSet, int) - Static method in class boone.util.Patterns
-
Reorders the first n patterns in this set randomly.
- Sigmoid() - Constructor for class boone.map.Function.Sigmoid
-
- Signum() - Constructor for class boone.map.Function.Signum
-
- SignumWithoutZero() - Constructor for class boone.map.Function.SignumWithoutZero
-
- sink - Variable in class boone.Link
-
The destination / sink unit.
- Sinus() - Constructor for class boone.map.Function.Sinus
-
- Sinus(double) - Constructor for class boone.map.Function.Sinus
-
- SITE - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- SITE_FUNCTION - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- SITE_NAME - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- SITE_SECTION_TITLE - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- SITES - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- size() - Method in class boone.PatternSet
-
Return the size of the pattern set, which is the number of input patterns.
- skipToNextLine() - Method in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
Advances the LA current position to the next EOL character.
- SNNS - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- snnsFileHeader - Static variable in class boone.io.SNNSNetFilter
-
SNNS file header
- SNNSNetFilter - Class in boone.io
-
Load and save SNNS net files.
- SNNSNetFilter() - Constructor for class boone.io.SNNSNetFilter
-
- SNNSNetFilter.ENSNNSLexicalAnalyzer - Class in boone.io
-
Lexical Analyser class.
- SNNSNetFilter.ENSNNSParser - Class in boone.io
-
Parser.
- SNNSPatternFilter - Class in boone.io
-
A filter for for SNNS pattern files.
- SNNSPatternFilter() - Constructor for class boone.io.SNNSPatternFilter
-
- SOFF - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- SoftMax() - Constructor for class boone.map.Function.SoftMax
-
- som - Variable in class boone.util.UMatrix
-
- SOMTrainer - Class in boone.training
-
The unsupervised SOM training algorithm implementing a simple dot product SOM with a linearly decreasing learn rate
and a linearly decreasing neighborhood radius.
- SOMTrainer(Topology) - Constructor for class boone.training.SOMTrainer
-
Creates the SOM Trainer.
- sortRandom() - Method in class boone.neurons.NeuronList
-
Returns this list of the given net with neurons in random order.
- sortTopological() - Method in class boone.neurons.NeuronList
-
Sorts the neuron's of a feed-forward network in topological order and assigns layer numbers
starting with 0 (input layer).
- source - Variable in class boone.Link
-
The source unit.
- SOURCE_FILES - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- SOURCE_WEIGHT - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-
- Spike - Class in boone.spike
-
This function is the default function that is used to describe the form of the spikes
generated by a SpikingNeuron in a SpikingNeuralNet.
- Spike() - Constructor for class boone.spike.Spike
-
Create a new Spike, with defaults for the parameters.
- Spike(double, double, double, double) - Constructor for class boone.spike.Spike
-
Create a new Spike, with the specified parameter values.
- SpikeEvent - Class in boone.spike
-
This event is generated by the SpikingLink and SpikingNeuron objects
in a SpikingNeuralNet, during the simulation of a spiking neural network.
- SpikeEvent() - Constructor for class boone.spike.SpikeEvent
-
Create a new SpikeEvent object, with no references and timestamp 0.
- SpikeEvent(double, BrainPart, BrainPart, Function, int) - Constructor for class boone.spike.SpikeEvent
-
Create a new SpikeEvent object, with the specified parameter values.
- SpikeEventBuffer - Class in boone.spike
-
The global buffer in a
SpikingNeuralNet that holds the events generated by the neurons
and links inside the network.
- SpikeEventBuffer() - Constructor for class boone.spike.SpikeEventBuffer
-
Create a new SpikeEventBuffer, with an infinite horizon.
- SpikeEventBuffer(double) - Constructor for class boone.spike.SpikeEventBuffer
-
Create a new SpikeEventBuffer, with the specified horizon.
- SpikeEventQueue - Class in boone.spike
-
Queue holding SpikeEvent objects, ordered according to their
timestamps.
- SpikeEventQueue() - Constructor for class boone.spike.SpikeEventQueue
-
Create a new SpikeEventQueue, with an infinite horizon.
- SpikeEventQueue(double) - Constructor for class boone.spike.SpikeEventQueue
-
Create a new SpikeEventQueue, with the specified horizon.
- SpikeSet - Class in boone.spike
-
A spike set links lists of doubles to specific neurons.
- SpikeSet() - Constructor for class boone.spike.SpikeSet
-
- SpikingLink - Class in boone.spike
-
- SpikingLink() - Constructor for class boone.spike.SpikingLink
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Create a new SpikingLink with defaults for the attributes.
- SpikingLink(Neuron, Neuron, double) - Constructor for class boone.spike.SpikingLink
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Create a new SpikingLink with the specified weight and delay = 0,
and add it to the link lists in the specified source and sink neurons.
- SpikingNeuralNet - Class in boone.spike
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The class SpikingNeuralNet represents a spiking neural network.
- SpikingNeuralNet() - Constructor for class boone.spike.SpikingNeuralNet
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Create a new, empty SpikingNeuralNet.
- SpikingNeuron - Class in boone.spike
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- SpikingNeuron() - Constructor for class boone.spike.SpikingNeuron
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Create a new SpikingNeuron with default spike form and a threshold of 15mV.
- SpikingNeuron(boolean, boolean, boolean) - Constructor for class boone.spike.SpikingNeuron
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Create a {new @code SpikingNeuron} with default spike form.
- SquareError - Class in boone.training
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The square error function is the default for training.
- SquareError() - Constructor for class boone.training.SquareError
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- ST - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
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- startRadius - Variable in class boone.training.SOMTrainer
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The initial neighborhood radius.
- stepMode - Variable in class boone.Trainer
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Indicates step-wise training.
- steps - Variable in class boone.training.SAETrainer
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The number of steps used for training
- stop() - Method in class boone.spike.SpikingNeuralNet
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Stop scheduling and propagating spikes.
- Storable - Interface in boone.io
-
Interface with methods to load and store an object instance's data from/to XML DOM.
- stream - Variable in class boone.util.StreamParser
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the input stream from which to read
- StreamParser - Class in boone.util
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Parse a stream, character by character.
- StreamParser(InputStream) - Constructor for class boone.util.StreamParser
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Constructs the parser with the given stream.
- streamSize - Variable in class boone.io.IOFilter
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The number of patterns read in a single stream event.
- strideHeight - Variable in class boone.structure.FilterMap
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The height of a stride.
- strideWidth - Variable in class boone.structure.FilterMap
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The width of a stride.
- STRING - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
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- stripOff(String, char) - Static method in class boone.util.Common
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Strips off all characters 'c' in string 's'.
- SUBNET - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
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- SUBNET_SECTION_TITLE - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
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- sumSquareError(NeuralNet, PatternSet) - Static method in class boone.training.NetError
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Calculate the Square Sum Error on the network.
- swap(List<E>, int, int) - Static method in class boone.util.Common
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Swaps the objects at the given positions in the list.
- swap(PatternSet, int, int) - Static method in class boone.util.Patterns
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Swaps the two patterns at position pos1 and pos2 of the given set including names, inputs, targets, and outputs.
- TanH() - Constructor for class boone.map.Function.TanH
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- TARGET - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
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- targets - Variable in class boone.PatternSet
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The target patterns.
- test(List<Double>, List<Double>) - Method in class boone.Trainer
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Test a given input pattern and return the error.
- test() - Method in class boone.Trainer
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Returns the error on the test data.
- test() - Method in class boone.training.SOMTrainer
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Returns the error on the programs pattern set by comparing the cluster of the winning neuron
to the cluster of the pattern.
- testData - Variable in class boone.Trainer
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- tickList - Variable in class boone.structure.NetCompiler.BooneCompiledNet
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Tick list, for random calculation order.
- TIME_DELAY_SECTION_TITLE - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
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- toArray() - Method in class boone.map.Position
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Convert to a float array.
- toArray(List<Double>) - Static method in class boone.util.Conversion
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Copies the list values to a new array with the size of the list.
- toBoolean(String, boolean) - Static method in class boone.util.Conversion
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Converts a string boolean to a boolean.
- toDouble(String, double) - Static method in class boone.util.Conversion
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Convert a stringified double to a double.
- TOFF - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
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- toFloat(String, float) - Static method in class boone.util.Conversion
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Converts a string float to a float.
- toInt(String, int) - Static method in class boone.util.Conversion
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Converts a string int to an int.
- toLong(String, long) - Static method in class boone.util.Conversion
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Converts a string long to a long.
- Topology - Class in boone.map
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The topology defines the neighborhood relation of the output neurons so as to form a map of neurons.
- Topology() - Constructor for class boone.map.Topology
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Creates the Topology.
- topology - Variable in class boone.NeuralNet
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The network topology.
- topology - Variable in class boone.training.SOMTrainer
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The topology of the SOM.
- topology - Variable in class boone.util.UMatrix
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- toString() - Method in class boone.BrainPart
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Returns the name of the BrainPart.
- toString() - Method in class boone.Link
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Return a string
- toString() - Method in class boone.map.Position
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Returns a string representation of this position.
- toString() - Method in class boone.NeuralNet
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convert the net to a string (multi-line).
- toString() - Method in class boone.Neuron
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Returns a string representation of the neuron.
- toString() - Method in class boone.neurons.NeuronList
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Returns a string representation of this neuron list.
- toString() - Method in class boone.PatternSet
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Returns a string representation of this pattern set.
- toString() - Method in class boone.spike.SpikeEvent
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- toString() - Method in class boone.spike.SpikeEventQueue
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- toString() - Method in class boone.spike.SpikingLink
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- toString() - Method in class boone.spike.SpikingNeuron
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- toString() - Method in class boone.structure.ConvolutionLayer
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Returns the width x height x depth of this layer.
- toString() - Method in class boone.structure.ConvolutionMap
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Returns the type(width x height) of this map.
- toString() - Method in class boone.structure.FeedForwardLayer
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Returns the width x height x depth of this layer.
- toString() - Method in class boone.structure.ForwardMap
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Returns the type(width x height) of this map.
- toString() - Method in class boone.structure.Layer
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Returns the maps of this layer.
- toString() - Method in class boone.structure.Map
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Returns the (width x height) of this map.
- toString() - Method in class boone.structure.PoolingLayer
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Returns the width x height x depth of this layer.
- toString() - Method in class boone.structure.PoolingMap
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Returns the width x height of this map.
- toString() - Method in class boone.Trainer
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- toXML(Element) - Method in class boone.Brain
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- toXML(Element) - Method in class boone.BrainPart
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Writes attributes to XML tree.
- toXML(Element) - Method in interface boone.io.Storable
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Writes attributes to XML tree.
- toXML(Element) - Method in class boone.Link
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Writes attributes to XML tree.
- toXML(Element) - Method in class boone.links.MultiLink
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Writes attributes to XML tree.
- toXML(Element) - Method in class boone.map.Function.AboutEqual
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- toXML(Element) - Method in class boone.map.Function.AtLeast
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Writes attribute to XML.
- toXML(Element) - Method in class boone.map.Function.AtMost
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Writes attributes to XML.
- toXML(Element) - Method in class boone.map.Function.CatmullRomSpline
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- toXML(Element) - Method in class boone.map.Function.Clip
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- toXML(Element) - Method in class boone.map.Function.Composition
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- toXML(Element) - Method in class boone.map.Function.GreaterThan
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- toXML(Element) - Method in class boone.map.Function.LessThan
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- toXML(Element) - Method in class boone.map.Function.NaturalSpline
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- toXML(Element) - Method in class boone.map.Function.Scaled
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- toXML(Element) - Method in class boone.map.Function.Sinus
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- toXML(Element) - Method in class boone.map.Function
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Adds a function element to XML.
- toXML(Element) - Method in class boone.map.HexagonTopology
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Writes specific attributes to XML tree.
- toXML(Element) - Method in class boone.map.Position
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Writes attributes to XML tree.
- toXML(Element) - Method in class boone.map.Topology
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Writes common topology attributes to a new child element.
- toXML(Element) - Method in class boone.NeuralNet
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Writes attributes to XML.
- toXML(Element) - Method in class boone.Neuron
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Writes attributes to XML tree.
- toXML(Element) - Method in class boone.neurons.NeuronList
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- toXML(Element) - Method in class boone.PatternSet
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Writes patterns to XML tree.
- toXML(Element) - Method in class boone.spike.PostsynapticPotential
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Writes specific attributes to XML tree.
- toXML(Element) - Method in class boone.spike.Spike
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Writes specific attributes to XML tree.
- toXML(Element) - Method in class boone.spike.SpikingLink
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Writes attributes to XML.
- toXML(Element) - Method in class boone.spike.SpikingNeuron
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Writes attributes to XML tree.
- toXML(Element) - Method in class boone.structure.Layer
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Returns an XML element containing information on the layer.
- toXML(Element) - Method in class boone.structure.Map
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Returns an XML element containing information on the layer.
- toXML(Element) - Method in class boone.Trainer
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Writes attributes to XML.
- toXML(Element) - Method in class boone.training.AdamTrainer
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Writes specific elements to XML tree.
- toXML(Element) - Method in class boone.training.LVQTrainer
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Writes specific attributes to XML tree.
- toXML(Element) - Method in class boone.training.RMSpropTrainer
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Writes specific elements to XML tree.
- toXML(Element) - Method in class boone.training.RpropTrainer
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Writes specific elements to XML tree.
- toXML(Element) - Method in class boone.training.SOMTrainer
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Writes specific attributes to XML tree.
- toXML(Element) - Method in class boone.training.TrainingSignalGenerator
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Writes attributes to XML tree.
- train() - Method in class boone.Trainer
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Performs training in the following order:
- train(List<Double>, List<Double>) - Method in class boone.Trainer
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Trains a single pattern once.
- train(List<Double>, List<Double>) - Method in class boone.training.BackpropTrainer
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Performs training of a single pattern with the following steps:
- train(Neuron) - Method in class boone.training.BackpropTrainer
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Accumulates the gradient of the neuron.
- train(Link) - Method in class boone.training.BackpropTrainer
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Calculates the error signal, back-propagates it to the source neuron, and accumulates the gradient information
of the link.
- train(List<Double>, List<Double>) - Method in class boone.training.HebbTrainer
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Hebbian learning of a single pattern.
- train(List<Double>, List<Double>) - Method in class boone.training.HopfieldDeltaTrainer
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Performs training of the Hopfield network.
- train(PatternSet, int) - Method in class boone.training.LVQTrainer
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Trains the SOM depending on the 'supervised' flag.
- train(List<Double>, List<Double>) - Method in class boone.training.SAETrainer
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- train() - Method in class boone.training.SAETrainer
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Training feed-forward network layer-wise to become auto-encoding.
- train(List<Double>, List<Double>) - Method in class boone.training.SOMTrainer
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Trains a single pattern once.
- train(Neuron, List<Double>, double) - Method in class boone.training.SOMTrainer
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Updates the weights from all input neurons to the given map neuron and normalizes the new weights.
- trainer - Variable in class boone.NeuralNet
-
The trainer for this network.
- Trainer - Class in boone
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The trainer super class for all training algorithms.
- Trainer() - Constructor for class boone.Trainer
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Constructs a trainer with squared error function (learn rate = 0.2, epochs = 1000).
- trainingData - Variable in class boone.Trainer
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The training data set.
- trainingSignalGenerator - Variable in class boone.Trainer
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The training signal generator.
- TrainingSignalGenerator - Class in boone.training
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This generator computes error signals for back-propagation and network errors.
- TrainingSignalGenerator() - Constructor for class boone.training.TrainingSignalGenerator
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- trainPattern(List<Double>, List<Double>) - Method in class boone.Trainer
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Trains a single pattern once and updates the weights.
- TRANSLATION_SECTION_TITLE - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
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- trimEnd(StringBuffer) - Method in class boone.util.StreamParser
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remove whitespace from the end of the given StringBuffer
- TYPE_NAME - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
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- TYPE_SECTION_TITLE - Static variable in class boone.io.SNNSNetFilter.ENSNNSLexicalAnalyzer
-