org.encog.neural.pattern
Class JordanPattern

java.lang.Object
  extended by org.encog.neural.pattern.JordanPattern
All Implemented Interfaces:
NeuralNetworkPattern

public class JordanPattern
extends Object
implements NeuralNetworkPattern

This class is used to generate an Jordan style recurrent neural network. This network type consists of three regular layers, an input output and hidden layer. There is also a context layer which accepts output from the output layer and outputs back to the hidden layer. This makes it a recurrent neural network. The Jordan neural network is useful for temporal input data. The specified activation function will be used on all layers. The Jordan neural network is similar to the Elman neural network.

Author:
jheaton

Constructor Summary
JordanPattern()
          Construct an object to create a Jordan type neural network.
 
Method Summary
 void addHiddenLayer(int count)
          Add a hidden layer, there should be only one.
 void clear()
          Clear out any hidden neurons.
 MLMethod generate()
          Generate a Jordan neural network.
 void setActivationFunction(ActivationFunction activation)
          Set the activation function to use on each of the layers.
 void setInputNeurons(int count)
          Set the number of input neurons.
 void setOutputNeurons(int count)
          Set the number of output neurons.
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

JordanPattern

public JordanPattern()
Construct an object to create a Jordan type neural network.

Method Detail

addHiddenLayer

public void addHiddenLayer(int count)
Add a hidden layer, there should be only one.

Specified by:
addHiddenLayer in interface NeuralNetworkPattern
Parameters:
count - The number of neurons in this hidden layer.

clear

public void clear()
Clear out any hidden neurons.

Specified by:
clear in interface NeuralNetworkPattern

generate

public MLMethod generate()
Generate a Jordan neural network.

Specified by:
generate in interface NeuralNetworkPattern
Returns:
A Jordan neural network.

setActivationFunction

public void setActivationFunction(ActivationFunction activation)
Set the activation function to use on each of the layers.

Specified by:
setActivationFunction in interface NeuralNetworkPattern
Parameters:
activation - The activation function.

setInputNeurons

public void setInputNeurons(int count)
Set the number of input neurons.

Specified by:
setInputNeurons in interface NeuralNetworkPattern
Parameters:
count - Neuron count.

setOutputNeurons

public void setOutputNeurons(int count)
Set the number of output neurons.

Specified by:
setOutputNeurons in interface NeuralNetworkPattern
Parameters:
count - Neuron count.


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