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## U

UnsupervisedHebbianLearning - Class in org.neuroph.nnet.learning
  Unsupervised hebbian learning rule.
UnsupervisedHebbianLearning() - Constructor for class org.neuroph.nnet.learning.UnsupervisedHebbianLearning
  Creates new instance of UnsupervisedHebbianLearning algorithm
UnsupervisedHebbianLearning(NeuralNetwork) - Constructor for class org.neuroph.nnet.learning.UnsupervisedHebbianLearning
  Creates an instance of UnsupervisedHebbianLearning algorithm for the specified neural network
UnsupervisedHebbianNetwork - Class in org.neuroph.nnet
  Hebbian neural network with unsupervised Hebbian learning algorithm.
UnsupervisedHebbianNetwork(int, int) - Constructor for class org.neuroph.nnet.UnsupervisedHebbianNetwork
  Creates an instance of Unsuervised Hebian net with specified number of neurons in input and output layer
UnsupervisedHebbianNetwork(int, int, TransferFunctionType) - Constructor for class org.neuroph.nnet.UnsupervisedHebbianNetwork
  Creates an instance of Unsuervised Hebian net with specified number of neurons in input layer and output layer, and transfer function
UnsupervisedLearning - Class in org.neuroph.core.learning
  Base class for all unsupervised learning algorithms.
UnsupervisedLearning() - Constructor for class org.neuroph.core.learning.UnsupervisedLearning
  Creates new unsupervised learning rule
UnsupervisedLearning(NeuralNetwork) - Constructor for class org.neuroph.core.learning.UnsupervisedLearning
  Creates new unsupervised learning rule and sets the neural network to train
updateNetworkWeights(Vector<Double>) - Method in class org.neuroph.core.learning.SupervisedLearning
  This method should implement the weights update procedure
updateNetworkWeights(Vector<Double>) - Method in class org.neuroph.nnet.learning.BackPropagation
  This method implements weight update procedure for the whole network for the specified error vector
updateNetworkWeights(Vector<Double>) - Method in class org.neuroph.nnet.learning.LMS
  This method implements weight update procedure for the whole network for this learning rule
updateNetworkWeights(Vector<Double>) - Method in class org.neuroph.nnet.learning.SigmoidDeltaRule
  This method implements weight update procedure for the whole network for this learning rule
updateNetworkWeights(Vector<Double>) - Method in class org.neuroph.nnet.learning.StepDeltaRule
  This method implements weight update procedure for the whole network for this learning rule
updateNetworkWeights(Vector<Double>) - Method in class org.neuroph.nnet.learning.SupervisedHebbianLearning
  This method implements weight update procedure for the whole network for this learning rule
updateNeuronWeights(Neuron) - Method in class org.neuroph.nnet.learning.BinaryHebbianLearning
  This method implements weights update procedure for the single neuron
updateNeuronWeights(Neuron) - Method in class org.neuroph.nnet.learning.InstarLearning
  This method implements weights update procedure for the single neuron
updateNeuronWeights(Neuron) - Method in class org.neuroph.nnet.learning.LMS
  This method implements weights update procedure for the single neuron
updateNeuronWeights(Neuron) - Method in class org.neuroph.nnet.learning.MomentumBackpropagation
  This method implements weights update procedure for the single neuron for the backpropagation with momentum factor
updateNeuronWeights(Neuron) - Method in class org.neuroph.nnet.learning.OjaLearning
  This method implements weights update procedure for the single neuron
updateNeuronWeights(Neuron) - Method in class org.neuroph.nnet.learning.OutstarLearning
  This method implements weights update procedure for the single neuron
updateNeuronWeights(Neuron, double) - Method in class org.neuroph.nnet.learning.SupervisedHebbianLearning
  This method implements weights update procedure for the single neuron
updateNeuronWeights(Neuron) - Method in class org.neuroph.nnet.learning.UnsupervisedHebbianLearning
  This method implements weights update procedure for the single neuron
updateTotalNetworkError(Vector<Double>) - Method in class org.neuroph.core.learning.SupervisedLearning
  Subclasses update total network error for each training pattern with this method.
updateTotalNetworkError(Vector<Double>) - Method in class org.neuroph.nnet.learning.LMS
  Updates total network error with specified pattern error vector

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