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java.lang.Objectorg.joone.engine.Layer
org.joone.engine.SimpleLayer
org.joone.engine.SigmoidLayer
public class SigmoidLayer
The output of a sigmoid layer neuron is the sum of the weighted input values, applied to a sigmoid function. This function is expressed mathematically as: y = 1 / (1 + e^-x) This has the effect of smoothly limiting the output within the range 0 and 1
parent,
parent,
implemented interface,
Serialized Form| Field Summary |
|---|
| 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 | |
|---|---|
SigmoidLayer()
The constructor |
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SigmoidLayer(java.lang.String ElemName)
The constructor |
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| Method Summary | |
|---|---|
void |
backward(double[] pattern)
Reverse transfer function of the component. |
void |
forward(double[] pattern)
This method accepts an array of values in input and forwards it according to the Sigmoid propagation pattern. |
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 |
double |
getFlatSpotConstant()
Gets the flat spot constant. |
Learner |
getLearner()
Deprecated. - Used only for backward compatibility |
double |
getMaximumState()
Return maximum value of a node in this layer |
double |
getMinimumState()
Return minimum value of a node in this layer |
void |
setFlatSpotConstant(double aConstant)
Sets the constant to overcome the flat spot problem. |
| Methods inherited from class org.joone.engine.SimpleLayer |
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getLearningRate, getLrate, getMomentum, setDimensions, setLrate, setMomentum, setMonitor |
| Methods inherited from class java.lang.Object |
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clone, equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
| Methods inherited from interface org.joone.engine.Learnable |
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getMonitor, initLearner |
| Methods inherited from interface org.joone.engine.NeuralLayer |
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addInputSynapse, addNoise, addOutputSynapse, check, copyInto, getAllInputs, getAllOutputs, getBias, getLayerName, getMonitor, getRows, isRunning, removeAllInputs, removeAllOutputs, removeInputSynapse, removeOutputSynapse, setAllInputs, setAllOutputs, setBias, setLayerName, setMonitor, setRows, start |
| Constructor Detail |
|---|
public SigmoidLayer()
public SigmoidLayer(java.lang.String ElemName)
ElemName - The name of the Layer| Method Detail |
|---|
public void backward(double[] pattern)
throws JooneRuntimeException
Layer
backward in class SimpleLayerpattern - input pattern on which to apply the transfer function
JooneRuntimeExceptionpublic double getDerivative(int i)
getDerivative in class Layer
public void forward(double[] pattern)
throws JooneRuntimeException
forward in class Layerpattern -
JooneRuntimeException - This Exception is a wrapper Exception when an Exception is thrown
while doing the maths.(double[])public Learner getLearner()
Layer
getLearner in interface LearnablegetLearner in class LayerLearnable.getLearner()public void setFlatSpotConstant(double aConstant)
aConstant - public double getFlatSpotConstant()
public double getDefaultState()
Layer
getDefaultState in class Layerpublic double getMinimumState()
Layer
getMinimumState in class Layerpublic double getMaximumState()
Layer
getMaximumState in class Layer
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