#include <IcaNet1.hpp>
Collaboration diagram for IcaNet1:

Purpose: Define a non-sphered ICA single cell neural net to get sub-gaussian or super-gaussian IC component.
Paper: "Simple Neural Models for Independent Component Analysis.",
Aapo Hyvarinen and Erkki Oja, 18/02/1997 , Report University of Technology, Helsinski.
"One Unit Learning Rules for Independent Component Analysis.",
Aapo Hyvarinen and Erkki Oja, 1997 , Helsinski.
@ Copyrights: Bernard De Cuyper & Eddy Fraiha 2003, Eggs & Pictures. MIT/Open BSD copyright model.
Public Methods | |
| IcaNet1 (double rate, bool superType) | |
| IcaNet1 (double rate, bool superType, bool combineFlag) | |
| virtual | ~IcaNet1 () |
| virtual RealVector * | getW () |
| virtual void | init (int size) |
| virtual void | learning (RealVector *sample, int nmax=1) |
| virtual double | forward (RealVector *src) |
| virtual void | output () |
Protected Methods | |
| virtual double | gMin (double u) |
| virtual double | gPlus (double u) |
| virtual void | learn (RealVector *sample) |
Private Attributes | |
| bool | combined |
| bool | superGaussian |
| double | learnRate |
| RealVector * | w |
| double | wNorm2 |
| RealVector * | dw |
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