Documentation API of the 'org.encog.neural.cpn.CPN' Java class
CPN
org.encog.neural.cpn

Class CPN

  • All Implemented Interfaces:
    Serializable, MLError, MLInput, MLInputOutput, MLMethod, MLOutput, MLProperties, MLRegression, MLResettable


    public class CPNextends BasicMLimplements MLRegression, MLResettable, MLError
    Counterpropagation Neural Networks (CPN) were developed by Professor Robert Hecht-Nielsen in 1987. CPN neural networks are a hybrid neural network, employing characteristics of both a feedforward neural network and a self-organzing map (SOM). The CPN is composed of three layers, the input, the instar and the outstar. The connection from the input to the instar layer is competitive, with only one neuron being allowed to win. The connection between the instar and outstar is feedforward. The layers are trained separately, using instar training and outstar training. The CPN network is good at regression.
    See Also:
    Serialized Form

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