Uses of Interface
org.joone.engine.LearnableLayer

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

Uses of LearnableLayer in org.joone.engine
 

Classes in org.joone.engine that implement LearnableLayer
 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.
 

Fields in org.joone.engine declared as LearnableLayer
protected  LearnableLayer AbstractLearner.learnableLayer
          The layer (biases) that is subjected to the learning process.
 

Methods in org.joone.engine that return LearnableLayer
 LearnableLayer AbstractLearner.getLayer()
          Gets the layer the learner is associated with.
 

Uses of LearnableLayer in org.joone.net
 

Classes in org.joone.net that implement LearnableLayer
 class NestedNeuralLayer
           
 

Uses of LearnableLayer in org.joone.structure
 

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



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