org.encog.neural.networks.layers

Class BasicLayer

java.lang.Object

org.encog.neural.flat.FlatLayer

org.encog.neural.networks.layers.BasicLayer

All Implemented Interfaces:

Serializable, Layer

public class BasicLayer
extends FlatLayer
implements Layer, Serializable

Basic functionality that most of the neural layers require. The basic layer is often used by itself to implement forward or recurrent layers. Other layer types are based on the basic layer as well. The following summarizes how basic layers calculate the output for a neural network. Example of a simple XOR network. Input: BasicLayer: 2 Neurons, null biasWeights, null biasActivation Hidden: BasicLayer: 2 Neurons, 2 biasWeights, 1 biasActivation Output: BasicLayer: 1 Neuron, 1 biasWeights, 1 biasActivation Input1Output and Input2Output are both provided. Synapse 1: Input to Hidden Hidden1Activation = (Input1Output * Input1->Hidden1Weight) + (Input2Output * Input2->Hidden1Weight) + (HiddenBiasActivation * Hidden1BiasWeight) Hidden1Output = calculate(Hidden1Activation, HiddenActivationFunction) Hidden2Activation = (Input1Output * Input1->Hidden2Weight) + (Input2Output * Input2->Hidden2Weight) + (HiddenBiasActivation * Hidden2BiasWeight) Hidden2Output = calculate(Hidden2Activation, HiddenActivationFunction) Synapse 2: Hidden to Output Output1Activation = (Hidden1Output * Hidden1->Output1Weight) + (Hidden2Output * Hidden2->Output1Weight) + (OutputBiasActivation * Output1BiasWeight) Output1Output = calculate(Output1Activation, OutputActivationFunction)

Author:

jheaton

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
BasicLayer(ActivationFunction activationFunction, boolean hasBias, int neuronCount) Construct this layer with a non-default activation function, also determine if a bias is desired or not.
BasicLayer(int neuronCount) Construct this layer with a sigmoid activation function.

Method Summary

Methods

Modifier and Type	Method and Description
ActivationFunction	getActivationFunction()
BasicNetwork	getNetwork()
int	getNeuronCount()
void	setNetwork(BasicNetwork network) Set the network for this layer.

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

getActivation, getBiasActivation, getContextCount, getContextFedBy, getCount, getTotalCount, hasBias, setActivation, setBiasActivation, setContextFedBy, toString

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.encog.neural.networks.layers.Layer

getBiasActivation, hasBias, setActivation, setBiasActivation

Constructor Detail

BasicLayer

public BasicLayer(ActivationFunction activationFunction,
          boolean hasBias,
          int neuronCount)

Construct this layer with a non-default activation function, also determine if a bias is desired or not.

Parameters:

activationFunction - The activation function to use.

neuronCount - How many neurons in this layer.

hasBias - True if this layer has a bias.

BasicLayer

public BasicLayer(int neuronCount)

Construct this layer with a sigmoid activation function.

Parameters:

neuronCount - How many neurons in this layer.

Method Detail

getNetwork

public BasicNetwork getNetwork()

Specified by:

getNetwork in interface Layer

Returns:

The network that owns this layer.

setNetwork

public void setNetwork(BasicNetwork network)

Set the network for this layer.

Specified by:

setNetwork in interface Layer

Parameters:

network - The network for this layer.

getNeuronCount

public int getNeuronCount()

Specified by:

getNeuronCount in interface Layer

Returns:

The neuron count.

getActivationFunction

public ActivationFunction getActivationFunction()

Specified by:

getActivationFunction in interface Layer

Returns:

The activation function used for this layer.