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java.lang.Objectca.nengo.math.impl.AbstractFunction
ca.nengo.model.plasticity.impl.AbstractSpikeLearningFunction
ca.nengo.model.plasticity.impl.InSpikeErrorFunction
public class InSpikeErrorFunction
A learning function that uses information from the ensemble to modulate the rate of synaptic change.
| Field Summary |
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| Fields inherited from class ca.nengo.model.plasticity.impl.AbstractSpikeLearningFunction |
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myLearningRate |
| Fields inherited from class ca.nengo.math.impl.AbstractFunction |
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DIMENSION_PROPERTY |
| Constructor Summary | |
|---|---|
InSpikeErrorFunction(float[] gain,
float[][] encoders)
Requires information from the post population to modulate learning. |
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InSpikeErrorFunction(float[] gain,
float[][] encoders,
float a2Minus,
float a3Minus,
float tauMinus,
float tauX)
Requires information from the post population to modulate learning. |
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InSpikeErrorFunction(NEFEnsembleImpl ens)
Extracts information from the post population to modulate learning. |
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| Method Summary | |
|---|---|
void |
afterDOmega(boolean[] preSpiking)
A function that is called after deltaOmega is evaluated. |
void |
beforeDOmega(boolean[] postSpiking)
A function that is called before deltaOmega is evaluated. |
InSpikeErrorFunction |
clone()
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protected float |
deltaOmega(float timeSinceDifferent,
float timeSinceSame,
float currentWeight,
float modInput,
int postIndex,
int preIndex,
int dim)
A learning rule that defines how the connection weight changes when a particular spike happens (either presynaptic spike or postsynaptic). |
void |
initActivityTraces(int postLength,
int preLength)
Initializes activity traces in the rule, if any exist. |
| Methods inherited from class ca.nengo.model.plasticity.impl.AbstractSpikeLearningFunction |
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getLearningRate, map, setLearningRate |
| Methods inherited from class ca.nengo.math.impl.AbstractFunction |
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getDimension, multiMap |
| Methods inherited from class java.lang.Object |
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equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
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public InSpikeErrorFunction(float[] gain,
float[][] encoders,
float a2Minus,
float a3Minus,
float tauMinus,
float tauX)
gain - Gain (scale) of the neurons in the post populationencoders - Encoders (phi tilde) of the neurons in the post populationa2Minus - Amplitude constant (see Pfister & Gerstner 2006)a3Minus - Amplitude constant (see Pfister & Gerstner 2006)tauMinus - Time constant (see Pfister & Gerstner 2006)tauX - Time constant (see Pfister & Gerstner 2006)
public InSpikeErrorFunction(float[] gain,
float[][] encoders)
gain - Gain (scale) of the neurons in the post populationencoders - Encoders (phi tilde) of the neurons in the post populationpublic InSpikeErrorFunction(NEFEnsembleImpl ens)
ens - Post population| Method Detail |
|---|
public void initActivityTraces(int postLength,
int preLength)
AbstractSpikeLearningFunction
initActivityTraces in class AbstractSpikeLearningFunctionpublic void beforeDOmega(boolean[] postSpiking)
AbstractSpikeLearningFunction
beforeDOmega in class AbstractSpikeLearningFunctionpostSpiking - An array representing whether or not neurons in the
population of interest are spiking.
protected float deltaOmega(float timeSinceDifferent,
float timeSinceSame,
float currentWeight,
float modInput,
int postIndex,
int preIndex,
int dim)
AbstractSpikeLearningFunction
deltaOmega in class AbstractSpikeLearningFunctiontimeSinceDifferent - The amount of time passed since the last spike
of the different type -- that is, if this is an onInSpike function, it would
be the amount of time since the last out spiketimeSinceSame - The amount of time passed since the last spike
of the same type -- that is, if this is an onInSpike function, it would
be the amount of time since the last in spikecurrentWeight - The current connection weight between the pre and post neuronsmodInput - The modulatory input, for this particular dimension (see dim)postIndex - The neuron index in the post-synaptic populationpreIndex - The neuron index in the pre-synaptic populationdim - The dimension of the modulatory inputAbstractSpikeLearningFunction.deltaOmega(float,float,float,float,int,int,int)public void afterDOmega(boolean[] preSpiking)
AbstractSpikeLearningFunction
afterDOmega in class AbstractSpikeLearningFunctionpreSpiking - An array representing whether or not neurons in the
population of interest are spiking.
public InSpikeErrorFunction clone()
throws java.lang.CloneNotSupportedException
clone in interface Functionclone in class AbstractSpikeLearningFunctionjava.lang.CloneNotSupportedExceptionObject.clone()
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