Class Hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:

[detail level 1234]

CSNAB::BenchmarkExec
CMNIST::CatHinge	Categorical hinge loss. Use if weights are restricted to be >0
Cmnist_helper::CONVOLUTION_LAYER
▼CMNIST::MLPBase	Base class for Multi Layer Networks (–> currently Perceptron only). Allows us to use polymorphism with templated class
CMNIST::MLP< Loss, ActivationFunction, Constraint >	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
CMNIST::MSE	Root Mean Squared Error
CMNIST::NoConstraint	Constraint for weights in neural network: No constraint
CSNAB::ParameterSweep
Cmnist_helper::POOLING_LAYER
CMNIST::PositiveLimitedWeights
CMNIST::PositiveWeights	Constraint for weights in neural network: Only weights >0
CMNIST::ReLU	ActivationFunction ReLU: Rectified Linear Unit
▼CSNAB::SNABBase	Virtual Base class for SNABs(Benchmarks). All SNABs should have seperate building of networks, execution and an evaluation tasks
▼CSNAB::GroupMaxFreqToGroup
CSNAB::GroupMaxFreqToGroupAllToAll
CSNAB::GroupMaxFreqToGroupProb
CSNAB::LateralInhibWTA
CSNAB::MaxInputAllToAll
▼CSNAB::MaxInputFixedOutConnector
CSNAB::MaxInputFixedInConnector
CSNAB::MaxInputOneToOne
CSNAB::MirrorInhibWTA
▼CSNAB::MNIST_BASE
CSNAB::MnistCNNPool
CSNAB::MnistDiehl
CSNAB::MnistDoubleCNN
▼CSNAB::MnistITLLastLayer
CSNAB::MnistITL
CSNAB::MnistNAS129
CSNAB::MnistNAS63
CSNAB::MnistNAStop
CSNAB::MnistSpikey
CSNAB::OutputFrequencyMultipleNeurons
CSNAB::OutputFrequencySingleNeuron
CSNAB::OutputFrequencySingleNeuron2
CSNAB::RefractoryPeriod
▼CSNAB::SetupTimeOneToOne
CSNAB::SetupTimeAllToAll
CSNAB::SetupTimeRandom
CSNAB::SimpleWTA
CSNAB::SingleMaxFreqToGroup
▼CSNAB::WeightDependentActivation
CSNAB::RateBasedWeightDependentActivation
CSNAB::Utilities	Collection of usefull Utilities not directly related to spiking networks
▼CConstraint
Cconvert_weights.WeightClip