#include <IcaNet2_0.hpp>
Collaboration diagram for IcaNet2_0:
Purpose: Define a 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 | |
IcaNet2_0 (double rate=0.1, double weight=0.1) | |
virtual | ~IcaNet2_0 () |
virtual RealVector * | getW () |
virtual bool | isSuperGaussian () |
virtual void | init (int size) |
virtual void | learning (RealVector *sample, int nmax=1) |
virtual double | forward (RealVector *src) |
virtual void | output () |
Protected Methods | |
virtual void | learn (RealVector *sample) |
Private Attributes | |
bool | superGaussian |
double | learnRate |
RealVector * | w |
double | wNorm2 |
RealVector * | dw |
double | v |
double | m4 |
double | kurt |