fastica.h File Reference

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

`#include <itpp/base/mat.h>`
`#include <itpp/itexports.h>`

Go to the source code of this file.

## Classes

class | itpp::Fast_ICA
| Fast_ICA Fast Independent Component Analysis (Fast ICA) More...

## Namespaces

namespace | itpp
| itpp namespace

## Macros

#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

Copyright (C) 1995-2010 (see AUTHORS file for a list of contributors)

This file is part of IT++ - a C++ library of mathematical, signal processing, speech processing, and communications classes and functions.

IT++ 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 3 of the License, or (at your option) any later version.

IT++ 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 IT++. If not, see http://www.gnu.org/licenses/.

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: first.nosp@m.name.nosp@m..last.nosp@m.name.nosp@m.@iris.nosp@m.a.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:

- no GUI
- return something even in the case of a convergence problem
- optimization of SVD decomposition (performed 2 times in Matlab, only 1 time in IT++)
- default approach is SYMM with non-linearity POW3

Definition in file fastica.h.

## Macro Definition Documentation

## FICA_APPROACH_DEFL

#define FICA_APPROACH_DEFL 2

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

Definition at line 69 of file fastica.h.

## FICA_APPROACH_SYMM

#define FICA_APPROACH_SYMM 1

Use symmetric approach : compute all ICs at a time.

Definition at line 71 of file fastica.h.

## FICA_NONLIN_POW3

#define FICA_NONLIN_POW3 10

Use x^3 non-linearity.

Definition at line 74 of file fastica.h.

## FICA_NONLIN_TANH

#define FICA_NONLIN_TANH 20

Use tanh(x) non-linearity.

Definition at line 76 of file fastica.h.

## FICA_NONLIN_GAUSS

#define FICA_NONLIN_GAUSS 30

Use Gaussian non-linearity.

Definition at line 78 of file fastica.h.

## FICA_NONLIN_SKEW

#define FICA_NONLIN_SKEW 40

Use skew non-linearity.

Definition at line 80 of file fastica.h.

## FICA_INIT_RAND

#define FICA_INIT_RAND 0

Set random start for Fast_ICA.

Definition at line 83 of file fastica.h.

## FICA_INIT_GUESS

#define FICA_INIT_GUESS 1

Set predefined start for Fast_ICA.

Definition at line 85 of file fastica.h.

## FICA_TOL

#define FICA_TOL 1e-9

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

Definition at line 88 of file fastica.h.

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