Neuroph

Package org.neuroph.nnet.learning

This package provides implementations of concrete neural network learning algorithms.

See:
          Description

Class Summary
BackPropagation The BackPropagation class is the Back Propagation learning rule for Multi Layer Perceptron neural networks.
BinaryHebbianLearning Hebbian-like learning algorithm used Hopfield network.
CompetitiveLearning The CompetitiveLearning class implements competitive learning rule.
HopfieldLearning The HopfieldLearning class implements learning algorithm for the Hopfield neural network.
InstarLearning The InstarLearning class implements hebbian-like learning rule for Instar network.
KohonenLearning The KohonenLearning implements the learning algorithm for Kohonen network.
LMS The LMS class implements LMS learning rule for neural networks.
MomentumBackpropagation The MomentumBackpropagation class implements backpropagation learning rule with momentum factor.
OjaLearning The OjaLearning class implements oja learning rule wich is a kind of unsupervised hebbian learning.
OutstarLearning The OutstarLearning class implements hebbian-like learning rule for Outstar network.
SigmoidDeltaRule The SigmoidDeltaRule class extends LMS learning rule an implements Delta rule learning algorithm for perceptrons with sigmoid functions.
StepDeltaRule The StepDeltaRule class implements Delta rule learning algorithm for perceptrons with step functions.
SupervisedHebbianLearning The SupervisedHebbianLearning class implements supervised hebbian learning rule.
UnsupervisedHebbianLearning The UnsupervisedHebbianLearning class implements unsupervised hebbian learning rule.
 

Package org.neuroph.nnet.learning Description

This package provides implementations of concrete neural network learning algorithms.


Neuroph