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fastica.h File Reference

Definition of FastICA (Independent Component Analysis) for IT++. More...

#include <itpp/base/mat.h>
#include <itpp/base/vec.h>

Go to the source code of this file.

Namespaces

namespace  itpp

Classes

class  itpp::Fast_ICA
 Fast_ICA Fast Independent Component Analysis (Fast ICA)

The software is based upon original FastICA for Matlab from A. Hyvarinen. Fast and Robust Fixed-Point Algorithms for Independent Component Analysis. IEEE Transactions on Neural Networks, 10(3), pp. 626-634, 1999. More...


Defines

#define FICA_APPROACH_DEFL   2
 Use deflation approach : compute IC one-by-one in a Gram-Schmidt-like fashion.
#define FICA_APPROACH_SYMM   1
 Use symmetric approach : compute all ICs at a time.
#define FICA_NONLIN_POW3   10
 Use x^3 non-linearity.
#define FICA_NONLIN_TANH   20
 Use tanh(x) non-linearity.
#define FICA_NONLIN_GAUSS   30
 Use Gaussian non-linearity.
#define FICA_NONLIN_SKEW   40
 Use skew non-linearity.
#define FICA_INIT_RAND   0
 Set random start for Fast_ICA.
#define FICA_INIT_GUESS   1
 Set predefined start for Fast_ICA.
#define FICA_TOL   1e-9
 Eigenvalues of the covariance matrix lower than FICA_TOL are discarded for analysis.


Detailed Description

Definition of FastICA (Independent Component Analysis) for IT++.

Author:
Francois Cayre and Teddy Furon
Date
2006-07-12 11:31:45 +0200 (śro, 12 lip 2006)
Revision
523

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IT++ - C++ library of mathematical, signal processing, speech processing, and communications classes and functions

Copyright (C) 1995-2006 (see AUTHORS file for a list of contributors)

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA

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This is IT++ implementation of the original Matlab package FastICA.

This code is Copyright (C) 2004 by: Francois CAYRE and Teddy FURON TEMICS Project INRIA/Rennes (IRISA) Campus Universitaire de Beaulieu 35042 RENNES cedex FRANCE

Email : firstname.lastname@irisa.fr

Matlab package is Copyright (C) 1998 by: Jarmo HURRI, Hugo GAVERT, Jaakko SARELA and Aapo HYVARINEN Laboratory of Information and Computer Science Helsinki University of Technology *

URL : http://www.cis.hut.fi/projects/ica/fastica/about.shtml

If you use results given by this FastICA software in an article for a scientific journal, conference proceedings or similar, please include the following original reference in the bibliography :

A. Hyvarinen, Fast and Robust Fixed-Point Algorithms for Independent Component Analysis, IEEE Transactions on Neural Networks 10(3):626-634, 1999

Differences with the original Matlab implementation:

Definition in file fastica.h.


Define Documentation

#define FICA_APPROACH_DEFL   2
 

Use deflation approach : compute IC one-by-one in a Gram-Schmidt-like fashion.

Definition at line 74 of file fastica.h.

Referenced by itpp::Fast_ICA::set_approach().

#define FICA_APPROACH_SYMM   1
 

Use symmetric approach : compute all ICs at a time.

Definition at line 76 of file fastica.h.

#define FICA_NONLIN_POW3   10
 

Use x^3 non-linearity.

Definition at line 79 of file fastica.h.

#define FICA_NONLIN_TANH   20
 

Use tanh(x) non-linearity.

Definition at line 81 of file fastica.h.

#define FICA_NONLIN_GAUSS   30
 

Use Gaussian non-linearity.

Definition at line 83 of file fastica.h.

#define FICA_NONLIN_SKEW   40
 

Use skew non-linearity.

Definition at line 85 of file fastica.h.

#define FICA_INIT_RAND   0
 

Set random start for Fast_ICA.

Definition at line 88 of file fastica.h.

#define FICA_INIT_GUESS   1
 

Set predefined start for Fast_ICA.

Definition at line 90 of file fastica.h.

Referenced by fpica().

#define FICA_TOL   1e-9
 

Eigenvalues of the covariance matrix lower than FICA_TOL are discarded for analysis.

Definition at line 93 of file fastica.h.

Referenced by pcamat().

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