Search Java Classes and Packages
#Org.neuroph.nnet.comp Classes and Interfaces - 18 results found.
| Name | Description | Type | Package | Framework |
| BiasNeuron | Neuron with constant high output (1), used as biasAuthor:Zoran Sevarac See Also:Neuron, | Class | org.neuroph.nnet.comp.neuron | Neuroph |
| CompetitiveLayer | Represents layer of competitive neurons, and provides methods for competition. | Class | org.neuroph.nnet.comp.layer | Neuroph |
| CompetitiveNetwork | Two layer neural network with competitive learning rule. | Class | org.neuroph.nnet | Neuroph |
| CompetitiveNeuron | Provides neuron behaviour specific for competitive neurons which are used in competitive layers, and networks with competitive learning. | Class | org.neuroph.nnet.comp.neuron | Neuroph |
| ConvolutionalLayer | Convolutional layer is a special type of layer, used in convolutional neural networks. | Class | org.neuroph.nnet.comp.layer | Neuroph |
| ConvolutionalUtils | Utility functions for convolutional networksAuthor:Boris Fulurija, Zorn Sevarac | Class | org.neuroph.nnet.comp | Neuroph |
| DelayedConnection | Represents the connection between neurons which can delay signal. | Class | org.neuroph.nnet.comp | Neuroph |
| DelayedNeuron | Provides behaviour for neurons with delayed output. | Class | org.neuroph.nnet.comp.neuron | Neuroph |
| FeatureMapsLayer | This class represents an array of feature maps which are 2 dimensional layers (Layer2D instances) and it is base class for Convolution and Pooling layers, | Class | org.neuroph.nnet.comp.layer | Neuroph |
| InputLayer | Represents a layer of input neurons - a typical neural network input layerAuthor:Zoran Sevarac See Also:InputNeuron, | Class | org.neuroph.nnet.comp.layer | Neuroph |
| InputMapsLayer | Input layer for convolutional networksAuthor:Boris Fulurija, Zoran SevaracSee Also:Serialized Form | Class | org.neuroph.nnet.comp.layer | Neuroph |
| InputNeuron | Provides input neuron behaviour - neuron with input extranaly set, which just transfer that input to output without change. | Class | org.neuroph.nnet.comp.neuron | Neuroph |
| InputOutputNeuron | Provides behaviour specific for neurons which act as input and the output neurons within the same layer. | Class | org.neuroph.nnet.comp.neuron | Neuroph |
| Kernel | Kernel used in convolution networks. | Class | org.neuroph.nnet.comp | Neuroph |
| Layer2D | 2D Layer provides 2D layout of the neurons in layer. | Class | org.neuroph.nnet.comp.layer | Neuroph |
| Layer2D .Dimensions | Dimensions (width and height) of the Layer2DSee Also:Serialized Form | Class | org.neuroph.nnet.comp.layer | Neuroph |
| PoolingLayer | Pooling layer is a special type of feature maps layer (FeatureMapsLayer) which is used in convolutional networks. | Class | org.neuroph.nnet.comp.layer | Neuroph |
| ThresholdNeuron | Provides behaviour for neurons with threshold. | Class | org.neuroph.nnet.comp.neuron | Neuroph |