ca.nengo.model.plasticity.impl
Class InSpikeErrorFunction
java.lang.Object
ca.nengo.math.impl.AbstractFunction
ca.nengo.model.plasticity.impl.AbstractSpikeLearningFunction
ca.nengo.model.plasticity.impl.InSpikeErrorFunction
- All Implemented Interfaces:
- Function, java.io.Serializable, java.lang.Cloneable
public class InSpikeErrorFunction
- extends AbstractSpikeLearningFunction
A learning function that uses information from the ensemble to modulate the rate
of synaptic change.
- Author:
- Trevor Bekolay
- See Also:
- Serialized Form
Constructor Summary |
InSpikeErrorFunction(float[] gain,
float[][] encoders)
Requires information from the post population to modulate learning. |
InSpikeErrorFunction(float[] gain,
float[][] encoders,
float a2Minus,
float a3Minus,
float tauMinus,
float tauX)
Requires information from the post population to modulate learning. |
InSpikeErrorFunction(NEFEnsembleImpl ens)
Extracts information from the post population to modulate learning. |
Method Summary |
InSpikeErrorFunction |
clone()
|
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). |
Methods inherited from class java.lang.Object |
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
InSpikeErrorFunction
public InSpikeErrorFunction(float[] gain,
float[][] encoders,
float a2Minus,
float a3Minus,
float tauMinus,
float tauX)
- Requires information from the post population to modulate learning.
- Parameters:
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)
InSpikeErrorFunction
public InSpikeErrorFunction(float[] gain,
float[][] encoders)
- Requires information from the post population to modulate learning.
- Parameters:
gain
- Gain (scale) of the neurons in the post populationencoders
- Encoders (phi tilde) of the neurons in the post population
InSpikeErrorFunction
public InSpikeErrorFunction(NEFEnsembleImpl ens)
- Extracts information from the post population to modulate learning.
- Parameters:
ens
- Post population
deltaOmega
protected float deltaOmega(float timeSinceDifferent,
float timeSinceSame,
float currentWeight,
float modInput,
int postIndex,
int preIndex,
int dim)
- Description copied from class:
AbstractSpikeLearningFunction
- A learning rule that defines how the connection weight changes when
a particular spike happens (either presynaptic spike or postsynaptic).
- Specified by:
deltaOmega
in class AbstractSpikeLearningFunction
- Parameters:
timeSinceDifferent
- 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 input- See Also:
AbstractSpikeLearningFunction.deltaOmega(float,float,float,float,int,int,int)
clone
public InSpikeErrorFunction clone()
throws java.lang.CloneNotSupportedException
- Specified by:
clone
in interface Function
- Overrides:
clone
in class AbstractSpikeLearningFunction
- Throws:
java.lang.CloneNotSupportedException
- See Also:
Object.clone()