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## C

calculate() - Method in class org.neuroph.contrib.IACNeuron
  Calculates neuron output
calculate() - Method in class org.neuroph.core.Layer
  Performs calculaton for all neurons in this layer
calculate() - Method in class org.neuroph.core.NeuralNetwork
  Performs calculation on whole network
calculate() - Method in class org.neuroph.core.Neuron
  Calculates neuron's output
calculate() - Method in class org.neuroph.nnet.comp.CompetitiveLayer
  Performs calculaton for all neurons in this layer
calculate() - Method in class org.neuroph.nnet.comp.CompetitiveNeuron
calculate() - Method in class org.neuroph.nnet.comp.DelayedNeuron
calculate() - Method in class org.neuroph.nnet.comp.InputOutputNeuron
  Calculates neuron output
calculate() - Method in class org.neuroph.nnet.comp.ThresholdNeuron
  Calculates neuron's output
clear() - Method in class org.neuroph.core.learning.TrainingSet
  Removes all alements from training set
ColorMode - Enum in org.neuroph.contrib.imgrec
  Represents the color modes for image recognition.
CompetitiveLayer - Class in org.neuroph.nnet.comp
  Represents layer of competitive neurons, and provides methods for competition.
CompetitiveLayer(int, NeuronProperties) - Constructor for class org.neuroph.nnet.comp.CompetitiveLayer
  Create an instance of CompetitiveLayer with the specified number of neurons with neuron properties
CompetitiveLearning - Class in org.neuroph.nnet.learning
  Competitive learning rule.
CompetitiveLearning() - Constructor for class org.neuroph.nnet.learning.CompetitiveLearning
  Creates new instance of CompetitiveLearning
CompetitiveLearning(NeuralNetwork) - Constructor for class org.neuroph.nnet.learning.CompetitiveLearning
  Creates new instance of CompetitiveLearning for the specified neural network
CompetitiveNetwork - Class in org.neuroph.nnet
  Two layer neural network with competitive learning rule.
CompetitiveNetwork(int, int) - Constructor for class org.neuroph.nnet.CompetitiveNetwork
  Creates new competitive network with specified neuron number
CompetitiveNeuron - Class in org.neuroph.nnet.comp
  Provides neuron behaviour specific for competitive neurons which are used in competitive layers, and networks with competitive learning.
CompetitiveNeuron(InputFunction, TransferFunction) - Constructor for class org.neuroph.nnet.comp.CompetitiveNeuron
  Creates an instance of CompetitiveNeuron with specified input and transfer functions
connectedNeuron - Variable in class org.neuroph.core.Connection
  Connected neuron
Connection - Class in org.neuroph.core
  Weighted connection to another neuron.
Connection(Neuron) - Constructor for class org.neuroph.core.Connection
  Creates a new connection to specified neuron with random weight
Connection(Neuron, Weight) - Constructor for class org.neuroph.core.Connection
  Creates a new connection to specified neuron with specified weight object
Connection(Neuron, double) - Constructor for class org.neuroph.core.Connection
  Creates a new connection to specified neuron with specified weight value
Connection(Neuron, Neuron) - Constructor for class org.neuroph.core.Connection
  Creates a new connection between specified neurons with random weight value
ConnectionFactory - Class in org.neuroph.util
  Provides methods to connect neurons by creating Connection objects.
ConnectionFactory() - Constructor for class org.neuroph.util.ConnectionFactory
convertRgbInputToBinaryBlackAndWhite(double[]) - Static method in class org.neuroph.contrib.imgrec.FractionRgbData
  Converts image rgb data to binary black and white data
convertToArray(Vector<Double>) - Static method in class org.neuroph.util.VectorParser
convertToVector(double[]) - Static method in class org.neuroph.util.VectorParser
createAdaline(int) - Static method in class org.neuroph.util.NeuralNetworkFactory
  Creates and returns a new instance of Adaline network
createBam(int, int) - Static method in class org.neuroph.util.NeuralNetworkFactory
  Creates and returns a new instance of BAM network
createBlackAndWhiteTrainingSet(List<String>, Map<String, FractionRgbData>) - Static method in class org.neuroph.contrib.imgrec.ImageRecognitionHelper
  Creates binary black and white training set for the specified image labels and rgb data
createCompetitiveNetwork(int, int) - Static method in class org.neuroph.util.NeuralNetworkFactory
  Creates and returns a new instance of competitive network
createConnection(Neuron, Neuron, double) - Method in class org.neuroph.core.NeuralNetwork
  Creates connection with specified weight value between specified neurons
createConnection(Neuron, Neuron) - Static method in class org.neuroph.util.ConnectionFactory
  Creates connection between two specified neurons
createConnection(Neuron, Neuron, Double) - Static method in class org.neuroph.util.ConnectionFactory
  Creates connection between two specified neurons
createConnection(Neuron, Neuron, Double, int) - Static method in class org.neuroph.util.ConnectionFactory
createConnection(Neuron, Neuron, Weight) - Static method in class org.neuroph.util.ConnectionFactory
  Creates connection between two specified neurons
createDemoNetwork() - Method in class org.neuroph.contrib.RecommenderNetwork
createHopfield(int) - Static method in class org.neuroph.util.NeuralNetworkFactory
  Creates and returns a new instance of Hopfield network
createInstar(int) - Static method in class org.neuroph.util.NeuralNetworkFactory
  Creates and returns a new instance of Instar network
createKohonen(int, int) - Static method in class org.neuroph.util.NeuralNetworkFactory
  Creates and returns a new instance of Kohonen network
createLayer(int, NeuronProperties) - Static method in class org.neuroph.util.LayerFactory
createLayer(int, TransferFunctionType) - Static method in class org.neuroph.util.LayerFactory
createLayer(Vector<NeuronProperties>) - Static method in class org.neuroph.util.LayerFactory
createMaxNet(int) - Static method in class org.neuroph.util.NeuralNetworkFactory
  Creates and returns a new instance of Max Net network
createMLPerceptron(String, TransferFunctionType) - Static method in class org.neuroph.util.NeuralNetworkFactory
  Creates and returns a new instance of Multi Layer Perceptron
createNeuron(NeuronProperties) - Static method in class org.neuroph.util.NeuronFactory
  Creates and returns neuron according to the given specification.
createNewNeuralNetwork(String, Dimension, ColorMode, List<String>, Vector<Integer>, TransferFunctionType) - Static method in class org.neuroph.contrib.imgrec.ImageRecognitionHelper
  Creates and returns new neural network for image recognition.
createOutstar(int) - Static method in class org.neuroph.util.NeuralNetworkFactory
  Creates and returns a new instance of Outstar network
createPerceptron(int, int, TransferFunctionType) - Static method in class org.neuroph.util.NeuralNetworkFactory
  Creates and returns a new instance of Perceptron network
createRbfNetwork(int, int, int) - Static method in class org.neuroph.util.NeuralNetworkFactory
  Creates and returns a new instance of RBF network
createSupervisedHebbian(int, int, TransferFunctionType) - Static method in class org.neuroph.util.NeuralNetworkFactory
  Creates and returns a new instance of Hebbian network
createTrainingSet(List<String>, Map<String, FractionRgbData>) - Static method in class org.neuroph.contrib.imgrec.ImageRecognitionHelper
  Creates training set for the specified image labels and rgb data
createUnsupervisedHebbian(int, int, TransferFunctionType) - Static method in class org.neuroph.util.NeuralNetworkFactory
  Creates and returns a new instance of Unsupervised Hebbian Network
currentIteration - Variable in class org.neuroph.core.learning.IterativeLearning
  Current iteration counter

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