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SNABSuite
0.x
Spiking Neural Architecture Benchmark Suite
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SNABSuite
0.x
Spiking Neural Architecture Benchmark Suite
|
| ▼Nconvert_weights | |
| CWeightClip | |
| ▼NMNIST | |
| CCatHinge | Categorical hinge loss. Use if weights are restricted to be >0 |
| CMLP | The standard densely connected multilayer Perceptron. Template arguments provide the loss function, the activation function of neurons (experimental) and a possible constraint for the weights |
| CMLPBase | Base class for Multi Layer Networks (–> currently Perceptron only). Allows us to use polymorphism with templated class |
| CMSE | Root Mean Squared Error |
| CNoConstraint | Constraint for weights in neural network: No constraint |
| CPositiveLimitedWeights | |
| CPositiveWeights | Constraint for weights in neural network: Only weights >0 |
| CReLU | ActivationFunction ReLU: Rectified Linear Unit |
| ▼Nmnist_helper | |
| CCONVOLUTION_LAYER | |
| CPOOLING_LAYER | |
| ▼NSNAB | |
| CBenchmarkExec | |
| CGroupMaxFreqToGroup | |
| CGroupMaxFreqToGroupAllToAll | |
| CGroupMaxFreqToGroupProb | |
| CLateralInhibWTA | |
| CMaxInputAllToAll | |
| CMaxInputFixedInConnector | |
| CMaxInputFixedOutConnector | |
| CMaxInputOneToOne | |
| CMirrorInhibWTA | |
| CMNIST_BASE | |
| CMnistCNNPool | |
| CMnistDiehl | |
| CMnistDoubleCNN | |
| CMnistITL | |
| CMnistITLLastLayer | |
| CMnistNAS129 | |
| CMnistNAS63 | |
| CMnistNAStop | |
| CMnistSpikey | |
| COutputFrequencyMultipleNeurons | |
| COutputFrequencySingleNeuron | |
| COutputFrequencySingleNeuron2 | |
| CParameterSweep | |
| CRateBasedWeightDependentActivation | |
| CRefractoryPeriod | |
| CSetupTimeAllToAll | |
| CSetupTimeOneToOne | |
| CSetupTimeRandom | |
| CSimpleWTA | |
| CSingleMaxFreqToGroup | |
| CSNABBase | Virtual Base class for SNABs(Benchmarks). All SNABs should have seperate building of networks, execution and an evaluation tasks |
| CUtilities | Collection of usefull Utilities not directly related to spiking networks |
| CWeightDependentActivation |
1.8.11
