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#Org.neuroph.nnet Classes and Interfaces - 61 results found.
NameDescriptionTypePackageFramework
AdalineAdaline neural network architecture with LMS learning rule.Classorg.neuroph.nnetNeuroph
AntiHebbianLearningA variant of Hebbian learning called Anti-Hebbian learning.Classorg.neuroph.nnet.learningNeuroph
AutoencoderNetworkClassorg.neuroph.nnetNeuroph
BackPropagationBack Propagation learning rule for Multi Layer Perceptron neural networks.Classorg.neuroph.nnet.learningNeuroph
BAMBidirectional Associative MemoryAuthor:Zoran Sevarac See Also:Serialized FormClassorg.neuroph.nnetNeuroph
BiasNeuronNeuron with constant high output (1), used as biasAuthor:Zoran Sevarac See Also:Neuron, Classorg.neuroph.nnet.comp.neuronNeuroph
BinaryDeltaRuleDelta rule learning algorithm for perceptrons with step functions.Classorg.neuroph.nnet.learningNeuroph
BinaryHebbianLearningHebbian-like learning algorithm used for Hopfield network.Classorg.neuroph.nnet.learningNeuroph
ClusterThis class represents a single cluster, with corresponding centroid and assigned vectorsAuthor:Zoran SevaracClassorg.neuroph.nnet.learning.kmeansNeuroph
CompetitiveLayerRepresents layer of competitive neurons, and provides methods for competition.Classorg.neuroph.nnet.comp.layerNeuroph
CompetitiveLearningCompetitive learning rule.Classorg.neuroph.nnet.learningNeuroph
CompetitiveNetworkTwo layer neural network with competitive learning rule.Classorg.neuroph.nnetNeuroph
CompetitiveNeuronProvides neuron behaviour specific for competitive neurons which are used in competitive layers, and networks with competitive learning.Classorg.neuroph.nnet.comp.neuronNeuroph
ConvolutionalBackpropagationClassorg.neuroph.nnet.learningNeuroph
ConvolutionalLayerConvolutional layer is a special type of layer, used in convolutional neural networks.Classorg.neuroph.nnet.comp.layerNeuroph
ConvolutionalNetworkConvolutional neural network with backpropagation algorithm modified for convolutional networks.Classorg.neuroph.nnetNeuroph
ConvolutionalUtilsUtility functions for convolutional networksAuthor:Boris Fulurija, Zorn SevaracClassorg.neuroph.nnet.compNeuroph
DelayedConnectionRepresents the connection between neurons which can delay signal.Classorg.neuroph.nnet.compNeuroph
DelayedNeuronProvides behaviour for neurons with delayed output.Classorg.neuroph.nnet.comp.neuronNeuroph
DynamicBackPropagationBackpropagation learning rule with dynamic learning rate and momentumAuthor:Zoran Sevarac See Also:Serialized FormClassorg.neuroph.nnet.learningNeuroph
ElmanNetworkUnder development: Learning rule BackProp Through Time requiredAuthor:zoranSee Also:Serialized FormClassorg.neuroph.nnetNeuroph
FeatureMapsLayerThis class represents an array of feature maps which are 2 dimensional layers (Layer2D instances) and it is base class for Convolution and Pooling layers, Classorg.neuroph.nnet.comp.layerNeuroph
GeneralizedHebbianLearningA variant of Hebbian learning called Generalized Hebbian learning.Classorg.neuroph.nnet.learningNeuroph
HopfieldHopfield neural network.Classorg.neuroph.nnetNeuroph
HopfieldLearningLearning algorithm for the Hopfield neural network.Classorg.neuroph.nnet.learningNeuroph
InputLayerRepresents a layer of input neurons - a typical neural network input layerAuthor:Zoran Sevarac See Also:InputNeuron, Classorg.neuroph.nnet.comp.layerNeuroph
InputMapsLayerInput layer for convolutional networksAuthor:Boris Fulurija, Zoran SevaracSee Also:Serialized FormClassorg.neuroph.nnet.comp.layerNeuroph
InputNeuronProvides input neuron behaviour - neuron with input extranaly set, which just transfer that input to output without change.Classorg.neuroph.nnet.comp.neuronNeuroph
InputOutputNeuronProvides behaviour specific for neurons which act as input and the output neurons within the same layer.Classorg.neuroph.nnet.comp.neuronNeuroph
InstarInstar neural network with Instar learning rule.Classorg.neuroph.nnetNeuroph
InstarLearningHebbian-like learning rule for Instar network.Classorg.neuroph.nnet.learningNeuroph
JordanNetworkUnder development: Learning rule BackProp Through Time requiredAuthor:zoranSee Also:Serialized FormClassorg.neuroph.nnetNeuroph
KernelKernel used in convolution networks.Classorg.neuroph.nnet.compNeuroph
KMeansClustering1.Classorg.neuroph.nnet.learning.kmeansNeuroph
KNearestNeighbour calculate distances to all vectors from list and find minimum vectorClassorg.neuroph.nnet.learning.knnNeuroph
KohonenKohonen neural network.Classorg.neuroph.nnetNeuroph
KohonenLearningLearning algorithm for Kohonen network.Classorg.neuroph.nnet.learningNeuroph
KVectorRepresents feature vector used in k-means clustering algorithmAuthor:Zoran Sevarac, Uros StojkicClassorg.neuroph.nnet.learning.kmeansNeuroph
Layer2D2D Layer provides 2D layout of the neurons in layer.Classorg.neuroph.nnet.comp.layerNeuroph
Layer2D .DimensionsDimensions (width and height) of the Layer2DSee Also:Serialized FormClassorg.neuroph.nnet.comp.layerNeuroph
LMSLMS learning rule for neural networks.Classorg.neuroph.nnet.learningNeuroph
MaxNetMax Net neural network with competitive learning rule.Classorg.neuroph.nnetNeuroph
MomentumBackpropagationBackpropagation learning rule with momentum.Classorg.neuroph.nnet.learningNeuroph
MultiLayerPerceptronMulti Layer Perceptron neural network with Back propagation learning algorithm.Classorg.neuroph.nnetNeuroph
NeuroFuzzyPerceptronThe NeuroFuzzyReasoner class represents Neuro Fuzzy Reasoner architecture.Classorg.neuroph.nnetNeuroph
OjaLearningOja learning rule wich is a modification of unsupervised hebbian learning.Classorg.neuroph.nnet.learningNeuroph
OutstarOutstar neural network with Outstar learning rule.Classorg.neuroph.nnetNeuroph
OutstarLearningHebbian-like learning rule for Outstar network.Classorg.neuroph.nnet.learningNeuroph
PerceptronPerceptron neural network with some LMS based learning algorithm.Classorg.neuroph.nnetNeuroph
PerceptronLearningPerceptron learning rule for perceptron neural networks.Classorg.neuroph.nnet.learningNeuroph
PoolingLayerPooling layer is a special type of feature maps layer (FeatureMapsLayer) which is used in convolutional networks.Classorg.neuroph.nnet.comp.layerNeuroph
RBFLearningLearning rule for Radial Basis Function networks.Classorg.neuroph.nnet.learningNeuroph
RBFNetworkRadial basis function neural network.Classorg.neuroph.nnetNeuroph
ResilientPropagationResilient Propagation learning rule used for Multi Layer Perceptron neural networks.Classorg.neuroph.nnet.learningNeuroph
SigmoidDeltaRuleDelta rule learning algorithm for perceptrons with sigmoid (or any other diferentiable continuous) functions.Classorg.neuroph.nnet.learningNeuroph
SimulatedAnnealingLearningThis class implements a simulated annealing learning rule for supervised neural networks.Classorg.neuroph.nnet.learningNeuroph
SupervisedHebbianLearningSupervised hebbian learning rule.Classorg.neuroph.nnet.learningNeuroph
SupervisedHebbianNetworkHebbian neural network with supervised Hebbian learning algorithm.Classorg.neuroph.nnetNeuroph
ThresholdNeuronProvides behaviour for neurons with threshold.Classorg.neuroph.nnet.comp.neuronNeuroph
UnsupervisedHebbianLearningUnsupervised hebbian learning rule.Classorg.neuroph.nnet.learningNeuroph
UnsupervisedHebbianNetworkHebbian neural network with unsupervised Hebbian learning algorithm.Classorg.neuroph.nnetNeuroph