Uses of Class
org.neuroph.core.Layer

Packages that use Layer

Package	Description
org.neuroph.core	Provides base classes and basic building components for neural networks.
org.neuroph.core.events	Provides neural network learning events system
org.neuroph.nnet	Provides out-of-the-box neural networks
org.neuroph.nnet.comp.layer	Provides various specific layer types
org.neuroph.util	Provides various utility classes for creating neural networks, type codes, parsing vectors, etc.
org.neuroph.util.random	Provides weights randomization techniques

Uses of Layer in org.neuroph.core

Fields in org.neuroph.core declared as Layer

Modifier and Type	Field and Description
protected Layer	Neuron.parentLayer Parent layer for this neuron

Methods in org.neuroph.core that return Layer

Modifier and Type	Method and Description
Layer	NeuralNetwork.getLayerAt(int index) Returns layer at specified index
Layer	Neuron.getParentLayer() Returns reference to parent layer for this neuron

Methods in org.neuroph.core that return types with arguments of type Layer

Modifier and Type	Method and Description
List<Layer>	NeuralNetwork.getLayers() Returns layers array

Methods in org.neuroph.core with parameters of type Layer

Modifier and Type	Method and Description
void	NeuralNetwork.addLayer(int index, Layer layer) Adds layer to specified index position in network
void	NeuralNetwork.addLayer(Layer layer) Adds layer to neural network
int	NeuralNetwork.indexOf(Layer layer) Returns index position of the specified layer
void	NeuralNetwork.removeLayer(Layer layer) Removes specified layer from network
void	Neuron.setParentLayer(Layer parent) Sets reference to parent layer for this neuron (layer in which the neuron is located)

Uses of Layer in org.neuroph.core.events

Constructors in org.neuroph.core.events with parameters of type Layer

Constructor and Description
NeuralNetworkEvent(Layer source, NeuralNetworkEvent.Type eventType)

Uses of Layer in org.neuroph.nnet

Methods in org.neuroph.nnet with parameters of type Layer

Modifier and Type	Method and Description
ConvolutionalNetwork.Builder	ConvolutionalNetwork.Builder.withFullConnectedLayer(Layer layer)

Uses of Layer in org.neuroph.nnet.comp.layer

Subclasses of Layer in org.neuroph.nnet.comp.layer

Modifier and Type	Class and Description
class	CompetitiveLayer Represents layer of competitive neurons, and provides methods for competition.
class	ConvolutionalLayer Convolutional layer is a special type of layer, used in convolutional neural networks.
class	FeatureMapLayer FeatureMapLayer Layer provides 2D layout of the neurons in layer.
class	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, which are used in ConvolutionalNetwork
class	InputLayer Represents a layer of input neurons - a typical neural network input layer
class	InputMapsLayer Input layer for convolutional networks
class	PoolingLayer Pooling layer is a special type of feature maps layer (FeatureMapsLayer) which is used in convolutional networks.

Uses of Layer in org.neuroph.util

Methods in org.neuroph.util that return Layer

Modifier and Type	Method and Description
static Layer	LayerFactory.createLayer(int neuronsCount, Class<? extends TransferFunction> transferFunctionClass)
static Layer	LayerFactory.createLayer(int neuronsCount, NeuronProperties neuronProperties) Creates and returns instance of Layer with specified number of neurons with specified properties
static Layer	LayerFactory.createLayer(int neuronsCount, TransferFunctionType transferFunctionType)
static Layer	LayerFactory.createLayer(List<NeuronProperties> neuronPropertiesVector)

Methods in org.neuroph.util with parameters of type Layer

Modifier and Type	Method and Description
static void	ConnectionFactory.createConnection(Neuron fromNeuron, Layer toLayer) Creates connectivity between specified neuron and all neurons in specified layer
static void	ConnectionFactory.forwardConnect(Layer fromLayer, Layer toLayer) Creates forward connection pattern between specified layers
static void	ConnectionFactory.forwardConnect(Layer fromLayer, Layer toLayer, double weightVal) Creates forward connectivity pattern between the specified layers
static void	ConnectionFactory.fullConnect(Layer layer) Creates full connectivity within layer - each neuron with all other within the same layer
static void	ConnectionFactory.fullConnect(Layer layer, double weightVal) Creates full connectivity within layer - each neuron with all other within the same layer with the specified weight values for all conections.
static void	ConnectionFactory.fullConnect(Layer layer, double weightVal, int delay) Creates full connectivity within layer - each neuron with all other within the same layer with the specified weight and delay values for all conections.
static void	ConnectionFactory.fullConnect(Layer fromLayer, Layer toLayer) Creates full connectivity between the two specified layers
static void	ConnectionFactory.fullConnect(Layer fromLayer, Layer toLayer, boolean connectBiasNeuron) Creates full connectivity between the two specified layers
static void	ConnectionFactory.fullConnect(Layer fromLayer, Layer toLayer, double weightVal) Creates full connectivity between two specified layers with specified weight for all connections

Uses of Layer in org.neuroph.util.random

Methods in org.neuroph.util.random with parameters of type Layer

Modifier and Type	Method and Description
protected void	WeightsRandomizer.randomize(Layer layer) Iterate and randomizes all neurons in specified layer