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 |
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. |
Methods inherited from class org.encog.neural.flat.FlatLayer |
getActivation, getBiasActivation, getContextCount, getContextFedBy, getCount, getTotalCount, hasBias, setActivation, setBiasActivation, setContextFedBy, toString |
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.
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.
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