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## D

dec(double) - Method in class org.neuroph.core.Weight
  Decreases the weight for specified amount
DelayedConnection - Class in org.neuroph.nnet.comp
  Represents the connection between neurons which can delay signal.
DelayedConnection(Neuron, double, int) - Constructor for class org.neuroph.nnet.comp.DelayedConnection
  Creates an instance of delayed connection to cpecified neuron and with specified weight
DelayedNeuron - Class in org.neuroph.nnet.comp
  Provides behaviour for neurons with delayed output.
DelayedNeuron(InputFunction, TransferFunction) - Constructor for class org.neuroph.nnet.comp.DelayedNeuron
  Creates an instance of neuron which can delay output
Diference - Class in org.neuroph.core.input
  Performs the vector difference operation on input and weight vector.
Diference() - Constructor for class org.neuroph.core.input.Diference
doIt() - Method in class org.neuroph.samples.timeseries.GenerateSet
  Does the data set generation
doLearningEpoch(TrainingSet) - Method in class org.neuroph.core.learning.IterativeLearning
  Override this method to implement specific learning epoch - one learning iteration, one pass through whole training set
doLearningEpoch(TrainingSet) - Method in class org.neuroph.core.learning.SupervisedLearning
  This method implements basic logic for one learning epoch for the supervised learning algorithms.
doLearningEpoch(TrainingSet) - Method in class org.neuroph.core.learning.UnsupervisedLearning
  This method does one learning epoch for the unsupervised learning rules.
doLearningEpoch(TrainingSet) - Method in class org.neuroph.nnet.learning.CompetitiveLearning
  This method does one learning epoch for the unsupervised learning rules.
doLearningEpoch(TrainingSet) - Method in class org.neuroph.nnet.learning.DynamicBackPropagation
doLearningEpoch(TrainingSet) - Method in class org.neuroph.nnet.learning.UnsupervisedHebbianLearning
  This method does one learning epoch for the unsupervised learning rules.
doOneLearningIteration(TrainingSet) - Method in class org.neuroph.core.learning.IterativeLearning
  Runs one learning iteration for the specified training set and notfies observers.
downSampleImage(Dimension, BufferedImage) - Static method in class org.neuroph.contrib.imgrec.ImageSampler
  Scales image to the specified dimension
downSampleImage(Dimension, BufferedImage, int) - Static method in class org.neuroph.contrib.imgrec.ImageSampler
  Scales image to the specified dimension
DynamicBackPropagation - Class in org.neuroph.nnet.learning
  Backpropagation learning rule with dynamic learning rate and momentum
DynamicBackPropagation() - Constructor for class org.neuroph.nnet.learning.DynamicBackPropagation
DynamicBackPropagation(NeuralNetwork) - Constructor for class org.neuroph.nnet.learning.DynamicBackPropagation

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