Package org.encog.engine.network.activation

Interface Summary

Interface	Description
ActivationFunction	This interface allows various activation functions to be used with the neural network.

Class Summary

Class	Description
ActivationBiPolar	BiPolar activation function.
ActivationBipolarSteepenedSigmoid	The bipolar sigmoid activation function is like the regular sigmoid activation function, except Bipolar sigmoid activation function.
ActivationClippedLinear	Linear activation function that bounds the output to [-1,+1].
ActivationCompetitive	An activation function that only allows a specified number, usually one, of the out-bound connection to win.
ActivationElliott	Computationally efficient alternative to ActivationSigmoid.
ActivationElliottSymmetric	Computationally efficient alternative to ActivationTANH.
ActivationGaussian	An activation function based on the Gaussian function.
ActivationLinear	The Linear layer is really not an activation function at all.
ActivationLOG	An activation function based on the logarithm function.
ActivationRamp	A ramp activation function.
ActivationReLU	A ramp activation function.
ActivationSigmoid	The sigmoid activation function takes on a sigmoidal shape.
ActivationSIN	An activation function based on the sin function, with a double period.
ActivationSoftMax	The softmax activation function.
ActivationSteepenedSigmoid	The Steepened Sigmoid is an activation function typically used with NEAT.
ActivationStep	The step activation function is a very simple activation function.
ActivationTANH	The hyperbolic tangent activation function takes the curved shape of the hyperbolic tangent.