org.encog.neural.flat
Class FlatNetworkRBF

java.lang.Object
  org.encog.neural.flat.FlatNetwork
      org.encog.neural.flat.FlatNetworkRBF

All Implemented Interfaces:

Serializable, Cloneable

public class FlatNetworkRBF
extends FlatNetwork
implements Serializable, Cloneable

A flat network designed to handle an RBF.

See Also:

Serialized Form

Field Summary

Fields inherited from class org.encog.neural.flat.FlatNetwork

DEFAULT_BIAS_ACTIVATION, NO_BIAS_ACTIVATION

Constructor Summary

FlatNetworkRBF()
Default constructor.

FlatNetworkRBF(int inputCount, int hiddenCount, int outputCount, RadialBasisFunction[] rbf)
Construct an RBF flat network.

Method Summary

FlatNetworkRBF	clone() Clone the network.
void	compute(double[] x, double[] output) Calculate the output for the given input.
RadialBasisFunction[]	getRBF()
void	setRBF(RadialBasisFunction[] rbf) Set the RBF's used.

Methods inherited from class org.encog.neural.flat.FlatNetwork

calculateError, clearConnectionLimit, clearContext, cloneFlatNetwork, computeLayer, decodeNetwork, encodeNetwork, getActivationFunctions, getBeginTraining, getBiasActivation, getConnectionLimit, getContextTargetOffset, getContextTargetSize, getEncodeLength, getEndTraining, getHasContext, getInputCount, getLayerContextCount, getLayerCounts, getLayerFeedCounts, getLayerIndex, getLayerOutput, getLayerSums, getNeuronCount, getOutputCount, getWeightIndex, getWeights, hasSameActivationFunction, init, isLimited, randomize, randomize, setActivationFunctions, setBeginTraining, setBiasActivation, setConnectionLimit, setContextTargetOffset, setContextTargetSize, setEndTraining, setHasContext, setInputCount, setLayerContextCount, setLayerCounts, setLayerFeedCounts, setLayerIndex, setLayerOutput, setLayerSums, setOutputCount, setWeightIndex, setWeights

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

FlatNetworkRBF

public FlatNetworkRBF()

Default constructor.

FlatNetworkRBF

public FlatNetworkRBF(int inputCount,
                      int hiddenCount,
                      int outputCount,
                      RadialBasisFunction[] rbf)

Construct an RBF flat network.

Parameters:

inputCount - The number of input neurons. (also the number of dimensions)

hiddenCount - The number of hidden neurons.

outputCount - The number of output neurons.

rbf - The radial basis functions to use.

Method Detail

clone

public FlatNetworkRBF clone()

Clone the network.

Overrides:

clone in class FlatNetwork

Returns:

A clone of the network.

compute

public void compute(double[] x,
                    double[] output)

Calculate the output for the given input.

Overrides:

compute in class FlatNetwork

Parameters:

x - The input.

output - Output will be placed here.

setRBF

public void setRBF(RadialBasisFunction[] rbf)

Set the RBF's used.

Parameters:

rbf - The RBF's used.

getRBF

public RadialBasisFunction[] getRBF()

Returns:

The RBF's used.