See: Description
| Class | Description |
|---|---|
| AbstractSigmoidalRule |
An abstract superclass for discrete and continuous time sigmoial squashing
function based update rules containing methods and variables common to
both.
|
| AdditiveRule |
AdditiveNeuron See Haykin (2002), section 14.5.
|
| AdExIFRule |
An implementation of adaptive exponential integrate and fire.
|
| BinaryRule |
BinaryNeuron takes one of two values.
|
| ContinuousSigmoidalRule |
Continuous Sigmoidal Rule provides various squashing function
ouputs for a neuron whose activation is numerically integrated continuously
over time.
|
| DecayRule |
DecayNeuron implements various forms of standard decay.
|
| FitzhughNagumo | |
| HodgkinHuxleyRule |
Hodgkin-Huxley Neuron.
|
| IACRule |
IACNeuron implements an Interactive Activation and Competition neuron.
|
| IntegrateAndFireRule |
IntegrateAndFireNeuron implements an integrate and fire neuron.
|
| IzhikevichRule |
IzhikevichNeuron.
|
| LinearRule |
LinearNeuron is a standard linear neuron.
|
| MorrisLecarRule | |
| NakaRushtonRule |
NakaRushtonNeuron is a firing-rate based neuron which is intended to
model spike rates of real neurons.
|
| PointNeuronRule |
PointNeuron from O'Reilley and Munakata, Computational Explorations in
Cognitive Neuroscience, chapter 2.
|
| RunningAverageRule |
RunningAverageNeuron keeps a running average of current and past
activity.
|
| SigmoidalRule |
SigmoidalRule provides various implementations of a standard
sigmoidal neuron.
|
| SpikingThresholdRule |
A simple spiking neuron that fires when weighted inputs exceed a threshold.
|
| ThreeValueRule |
ThreeValuedNeuron is a natural extension of a binary neuron, which
takes one of three values depending on the inputs to the neuron in relation
to two thresholds.
|
| TimedAccumulatorRule |
| Enum | Description |
|---|---|
| PointNeuronRule.OutputFunction |
Output functions.
|