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GeNN
3.3.0
GPU enhanced Neuronal Networks (GeNN)
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GeNN
3.3.0
GPU enhanced Neuronal Networks (GeNN)
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| ▼NCurrentSourceModels | |
| CBase | Base class for all current source models |
| CDC | DC source |
| CGaussianNoise | Noisy current source with noise drawn from normal distribution |
| ▼Ngenerate_swig_interfaces | |
| CCppBlockScope | |
| CSwigAsIsScope | |
| CSwigExtendScope | |
| CSwigInitScope | |
| CSwigInlineScope | |
| CSwigModuleGenerator | A helper class for generating SWIG interface files |
| ▼NInitSparseConnectivitySnippet | Base class for all sparse connectivity initialisation snippets |
| CBase | |
| CFixedProbability | |
| CFixedProbabilityBase | |
| CFixedProbabilityNoAutapse | |
| CInit | |
| COneToOne | Initialises connectivity to a 'one-to-one' diagonal matrix |
| CUninitialised | Used to mark connectivity as uninitialised - no initialisation code will be run |
| ▼NInitVarSnippet | Base class for all value initialisation snippets |
| CBase | |
| CConstant | Initialises variable to a constant value |
| CExponential | Initialises variable by sampling from the exponential distribution |
| CGamma | Initialises variable by sampling from the exponential distribution |
| CNormal | Initialises variable by sampling from the normal distribution |
| CUniform | Initialises variable by sampling from the uniform distribution |
| CUninitialised | Used to mark variables as uninitialised - no initialisation code will be run |
| ▼NNeuronModels | |
| CBase | Base class for all neuron models |
| CIzhikevich | Izhikevich neuron with fixed parameters [1] |
| CIzhikevichVariable | Izhikevich neuron with variable parameters [1] |
| CLegacyWrapper | Wrapper around legacy weight update models stored in nModels array of neuronModel objects |
| CPoisson | Poisson neurons |
| CPoissonNew | Poisson neurons |
| CRulkovMap | Rulkov Map neuron |
| CSpikeSource | Empty neuron which allows setting spikes from external sources |
| CSpikeSourceArray | Spike source array |
| CTraubMiles | Hodgkin-Huxley neurons with Traub & Miles algorithm |
| CTraubMilesAlt | Hodgkin-Huxley neurons with Traub & Miles algorithm |
| CTraubMilesFast | Hodgkin-Huxley neurons with Traub & Miles algorithm: Original fast implementation, using 25 inner iterations |
| CTraubMilesNStep | Hodgkin-Huxley neurons with Traub & Miles algorithm |
| ▼NNewModels | |
| CBase | Base class for all models - in addition to the parameters snippets have, models can have state variables |
| CLegacyWrapper | Wrapper around old-style models stored in global arrays and referenced by index |
| CVarInit | |
| CVarInitContainerBase | |
| CVarInitContainerBase< 0 > | |
| ▼NPostsynapticModels | |
| CBase | Base class for all postsynaptic models |
| CDeltaCurr | Simple delta current synapse |
| CExpCond | Exponential decay with synaptic input treated as a conductance value |
| CLegacyWrapper | |
| ▼Npygenn | |
| ►Ngenn_groups | |
| ►Ngenn_model | |
| ►Ngenn_wrapper | |
| ►Nmodel_preprocessor | |
| ▼NSnippet | |
| CBase | Base class for all code snippets |
| CInit | |
| CValueBase | |
| CValueBase< 0 > | |
| ▼NWeightUpdateModels | |
| CBase | Base class for all weight update models |
| CLegacyWrapper | Wrapper around legacy weight update models stored in weightUpdateModels array of weightUpdateModel objects |
| CPiecewiseSTDP | This is a simple STDP rule including a time delay for the finite transmission speed of the synapse |
| CStaticGraded | Graded-potential, static synapse |
| CStaticPulse | Pulse-coupled, static synapse |
| CStaticPulseDendriticDelay | Pulse-coupled, static synapse with heterogenous dendritic delays |
| ▼CCodeStream | Helper class for generating code - automatically inserts brackets, indents etc |
| CCB | A close bracket marker |
| COB | An open bracket marker |
| CScope | |
| CCStopWatch | Helper class for timing sections of host code in a cross-plarform manner |
| CCurrentSource | |
| Cdpclass | |
| CexpDecayDp | Class defining the dependent parameter for exponential decay |
| CFunctionTemplate | |
| CGenericFunction | |
| CNameIterCtx | |
| CNeuronGroup | |
| CneuronModel | Class for specifying a neuron model |
| CNNmodel | |
| CPairKeyConstIter | Custom iterator for iterating through the keys of containers containing pairs |
| CpostSynModel | Class to hold the information that defines a post-synaptic model (a model of how synapses affect post-synaptic neuron variables, classically in the form of a synaptic current). It also allows to define an equation for the dynamics that can be applied to the summed synaptic input variable "insyn" |
| CpwSTDP | TODO This class definition may be code-generated in a future release |
| CRaggedProjection | Row-major ordered sparse matrix structure in 'ragged' format |
| Crulkovdp | Class defining the dependent parameters of the Rulkov map neuron |
| CSparseProjection | Class (struct) for defining a spars connectivity projection |
| CstopWatch | |
| CSynapseGroup | |
| CweightUpdateModel | Class to hold the information that defines a weightupdate model (a model of how spikes affect synaptic (and/or) (mostly) post-synaptic neuron variables. It also allows to define changes in response to post-synaptic spikes/spike-like events |
1.8.13