Uses of Class
org.neuroph.core.NeuralNetwork

Packages that use NeuralNetwork
org.neuroph.core Provides base classes and basic building components for neural networks. 
org.neuroph.core.learning Provides base classes for neural network learning algorithms. 
org.neuroph.nnet Provides out-of-the-box neural networks 
org.neuroph.nnet.learning Provides implementations of specific neural network learning algorithms. 
org.neuroph.util Provides various utility classes for creating neural networks, type codes, parsing vectors, etc. 
org.neuroph.util.io Provides input/output adapters for file, JDBC, URL, stream 
org.neuroph.util.plugins Provides various plugins for neural networks. 
org.neuroph.util.random Provides weights randomization techniques 
 

Uses of NeuralNetwork in org.neuroph.core
 

Methods in org.neuroph.core that return NeuralNetwork
 NeuralNetwork Layer.getParentNetwork()
          Returns reference to parent network
static NeuralNetwork NeuralNetwork.load(InputStream inputStream)
          Loads neural network from the specified InputStream.
static NeuralNetwork NeuralNetwork.load(String filePath)
          Loads neural network from the specified file.
 

Methods in org.neuroph.core with parameters of type NeuralNetwork
 void Layer.setParentNetwork(NeuralNetwork parent)
          Sets reference on parent network
 

Uses of NeuralNetwork in org.neuroph.core.learning
 

Fields in org.neuroph.core.learning declared as NeuralNetwork
protected  NeuralNetwork LearningRule.neuralNetwork
          Neural network to train
 

Methods in org.neuroph.core.learning that return NeuralNetwork
 NeuralNetwork LearningRule.getNeuralNetwork()
          Gets neural network
 

Methods in org.neuroph.core.learning with parameters of type NeuralNetwork
 void LearningRule.setNeuralNetwork(NeuralNetwork neuralNetwork)
          Sets neural network for this learning rule
 

Uses of NeuralNetwork in org.neuroph.nnet
 

Subclasses of NeuralNetwork in org.neuroph.nnet
 class Adaline
          Adaline neural network architecture with LMS learning rule.
 class BAM
          Bidirectional Associative Memory
 class CompetitiveNetwork
          Two layer neural network with competitive learning rule.
 class Hopfield
          Hopfield neural network.
 class Instar
          Instar neural network with Instar learning rule.
 class Kohonen
          Kohonen neural network.
 class MaxNet
          Max Net neural network with competitive learning rule.
 class MultiLayerPerceptron
          Multi Layer Perceptron neural network with Back propagation learning algorithm.
 class NeuroFuzzyPerceptron
          The NeuroFuzzyReasoner class represents Neuro Fuzzy Reasoner architecture.
 class Outstar
          Outstar neural network with Outstar learning rule.
 class Perceptron
          Perceptron neural network with some LMS based learning algorithm.
 class RbfNetwork
          Radial basis function neural network.
 class SupervisedHebbianNetwork
          Hebbian neural network with supervised Hebbian learning algorithm.
 class UnsupervisedHebbianNetwork
          Hebbian neural network with unsupervised Hebbian learning algorithm.
 

Uses of NeuralNetwork in org.neuroph.nnet.learning
 

Fields in org.neuroph.nnet.learning declared as NeuralNetwork
protected  NeuralNetwork SimulatedAnnealingLearning.network
          The neural network that is to be trained.
 

Methods in org.neuroph.nnet.learning that return NeuralNetwork
 NeuralNetwork SimulatedAnnealingLearning.getNetwork()
          Get the best network from the training.
 

Methods in org.neuroph.nnet.learning with parameters of type NeuralNetwork
 void KohonenLearning.setNeuralNetwork(NeuralNetwork neuralNetwork)
           
 

Constructors in org.neuroph.nnet.learning with parameters of type NeuralNetwork
SimulatedAnnealingLearning(NeuralNetwork network)
           
SimulatedAnnealingLearning(NeuralNetwork network, double startTemp, double stopTemp, int cycles)
          Construct a simulated annleaing trainer for a feedforward neural network.
 

Uses of NeuralNetwork in org.neuroph.util
 

Methods in org.neuroph.util with parameters of type NeuralNetwork
static void NeuralNetworkCODEC.array2network(double[] array, NeuralNetwork network)
          Decode a network from an array.
static int NeuralNetworkCODEC.determineArraySize(NeuralNetwork network)
          Determine the array size for the given neural network.
static void NeuralNetworkCODEC.network2array(NeuralNetwork network, double[] array)
          Encode a network to an array.
static void NeuralNetworkFactory.setDefaultIO(NeuralNetwork nnet)
          Sets default input and output neurons for network (first layer as input, last as output)
 

Uses of NeuralNetwork in org.neuroph.util.io
 

Methods in org.neuroph.util.io with parameters of type NeuralNetwork
static void IOHelper.process(NeuralNetwork neuralNet, InputAdapter in, OutputAdapter out)
          Feeds specified neural network with data from InputAdapter and writes output using OutputAdapter
 

Uses of NeuralNetwork in org.neuroph.util.plugins
 

Methods in org.neuroph.util.plugins that return NeuralNetwork
 NeuralNetwork PluginBase.getParentNetwork()
          Returns the parent network for this plugin
 

Methods in org.neuroph.util.plugins with parameters of type NeuralNetwork
 void PluginBase.setParentNetwork(NeuralNetwork parentNetwork)
          Sets the parent network for this plugin
 

Uses of NeuralNetwork in org.neuroph.util.random
 

Methods in org.neuroph.util.random with parameters of type NeuralNetwork
 void WeightsRandomizer.randomize(NeuralNetwork neuralNetwork)
          Iterate all layers, neurons and connections in network, and randomize connection weights
 void NguyenWidrowRandomizer.randomize(NeuralNetwork neuralNetwork)
           
 void DistortRandomizer.randomize(NeuralNetwork neuralNetwork)
          Iterate all layers, neurons and connection weight and apply distort randomization
 



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