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java.lang.Objectorg.joone.engine.Layer
org.joone.engine.RbfLayer
org.joone.engine.RbfGaussianLayer
public class RbfGaussianLayer
This class implements the nonlinear layer in Radial Basis Function (RBF) networks using Gaussian functions.
Field Summary |
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Fields inherited from class org.joone.engine.Layer |
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bias, gradientInps, gradientOuts, inps, inputPatternListeners, learnable, learning, m_batch, monitor, myLearner, outputPatternListeners, outs, running, step, STOP_FLAG |
Constructor Summary | |
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RbfGaussianLayer()
Creates a new instance of RbfGaussianLayer |
Method Summary | |
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protected void |
backward(double[] pattern)
Reverse transfer function of the component. |
protected void |
forward(double[] pattern)
Transfer function to recall a result on a trained net |
double |
getDefaultState()
Return the default state of a node in this layer, such as 0 for a tanh or 0.5 for a sigmoid layer |
double |
getDerivative(int i)
Similar to the backward message and used by RTRL |
RbfGaussianParameters[] |
getGaussianParameters()
Gets the parameters that define the Gaussian RBFs. |
double |
getMaximumState()
Return maximum value of a node in this layer |
double |
getMinimumState()
Return minimum value of a node in this layer |
java.util.Collection |
Inspections()
It doesn't make sense to return biases for this layer |
protected void |
setDimensions()
Sets the dimension of the layer. |
void |
setGaussianParameters(RbfGaussianParameters[] aGaussianParameters)
Sets the parameters that define the Gaussian RBFs. |
void |
useRandomCenter(StreamInputSynapse aStreamInput)
Sets the Gaussian parameters to centers chosen randomly from the input/training data. |
Methods inherited from class org.joone.engine.RbfLayer |
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adjustSizeToFwdPattern |
Methods inherited from class java.lang.Object |
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clone, equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public RbfGaussianLayer()
Method Detail |
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protected void backward(double[] pattern) throws JooneRuntimeException
Layer
backward
in class Layer
pattern
- input pattern on which to apply the transfer function
JooneRuntimeException
public double getDerivative(int i)
getDerivative
in class Layer
protected void forward(double[] pattern) throws JooneRuntimeException
Layer
forward
in class Layer
pattern
- input pattern to which to apply the rtransfer function
JooneRuntimeException
protected void setDimensions()
Layer
setDimensions
in class RbfLayer
public RbfGaussianParameters[] getGaussianParameters()
public void setGaussianParameters(RbfGaussianParameters[] aGaussianParameters)
aGaussianParameters
- The new parameters for the RBFs.public void useRandomCenter(StreamInputSynapse aStreamInput)
aStreamInput
- the synapse providing the input, from where we will select random centers.public java.util.Collection Inspections()
Inspections
in interface Inspectable
Inspections
in class Layer
org.joone.Inspection
public double getDefaultState()
Layer
getDefaultState
in class Layer
public double getMinimumState()
Layer
getMinimumState
in class Layer
public double getMaximumState()
Layer
getMaximumState
in class Layer
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