Uses of Interface
org.joone.engine.NeuralLayer

Packages that use NeuralLayer
org.joone.engine   
org.joone.net   
org.joone.structure   
 

Uses of NeuralLayer in org.joone.engine
 

Subinterfaces of NeuralLayer in org.joone.engine
 interface LearnableLayer
           
 

Classes in org.joone.engine that implement NeuralLayer
 class BiasedLinearLayer
          This layer consists of linear neurons, i.e.
 class ContextLayer
          The context layer is similar to the linear layer except that it has an auto-recurrent connection between its output and input.
 class DelayLayer
          Delay unit to create temporal windows from time series
O---> Yk(t-N)
|
...
 class GaussianLayer
          This layer implements the Gaussian Neighborhood SOM strategy.
 class GaussLayer
          The output of a Gauss(ian) layer neuron is the sum of the weighted input values, applied to a gaussian curve (exp(- x * x)).
 class Layer
          The Layer object is the basic element forming the neural net.
 class LinearLayer
          The output of a linear layer neuron is the sum of the weighted input values, scaled by the beta parameter.
 class LogarithmicLayer
          This layer implements a logarithmic transfer function.
 class MemoryLayer
           
 class RbfGaussianLayer
          This class implements the nonlinear layer in Radial Basis Function (RBF) networks using Gaussian functions.
 class RbfLayer
          This is the basis (helper) for radial basis function layers.
 class SigmoidLayer
          The output of a sigmoid layer neuron is the sum of the weighted input values, applied to a sigmoid function.
 class SimpleLayer
          This abstract class represents layers that are composed by neurons that implement some transfer function.
 class SineLayer
          The output of a sine layer neuron is the sum of the weighted input values, applied to a sine (sin(x)).
 class SoftmaxLayer
          The outputs of the Softmax layer must be interpreted as probabilities.
 class TanhLayer
          Layer that applies the tangent hyperbolic transfer function to its input patterns
 class WTALayer
          This layer implements the Winner Takes All SOM strategy.
 

Methods in org.joone.engine that return NeuralLayer
 NeuralLayer Layer.copyInto(NeuralLayer newLayer)
          Copies one layer into another, to obtain a type-transformation from one kind of Layer to another.
 NeuralLayer NeuralLayer.copyInto(NeuralLayer newLayer)
          Copies a Layer into another one, to obtain a type-transformation from a kind of Layer to another.
 

Methods in org.joone.engine with parameters of type NeuralLayer
 NeuralLayer Layer.copyInto(NeuralLayer newLayer)
          Copies one layer into another, to obtain a type-transformation from one kind of Layer to another.
 NeuralLayer NeuralLayer.copyInto(NeuralLayer newLayer)
          Copies a Layer into another one, to obtain a type-transformation from a kind of Layer to another.
 

Uses of NeuralLayer in org.joone.net
 

Classes in org.joone.net that implement NeuralLayer
 class NestedNeuralLayer
           
 class NeuralNet
          This object represents a container of a neural network, giving to the developer the possibility to manage a neural network as a whole.
 

Methods in org.joone.net that return NeuralLayer
 NeuralLayer NeuralNet.copyInto(NeuralLayer p1)
          Not implemented.
 NeuralLayer NestedNeuralLayer.copyInto(NeuralLayer p1)
           
 

Methods in org.joone.net with parameters of type NeuralLayer
 NeuralLayer NeuralNet.copyInto(NeuralLayer p1)
          Not implemented.
 NeuralLayer NestedNeuralLayer.copyInto(NeuralLayer p1)
           
 

Uses of NeuralLayer in org.joone.structure
 

Classes in org.joone.structure that implement NeuralLayer
 class NetworkLayer
          Wraps an existing joone network into a single layer.
 



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