Definition of FastICA (Independent Component Analysis) for IT++. More...
|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...|
|itpp namespace |
|Use deflation approach : compute IC one-by-one in a Gram-Schmidt-like fashion. |
|Use symmetric approach : compute all ICs at a time. |
|Use x^3 non-linearity. |
|Use tanh(x) non-linearity. |
|Use Gaussian non-linearity. |
|Use skew non-linearity. |
|Set random start for Fast_ICA. |
|Set predefined start for Fast_ICA. |
|Eigenvalues of the covariance matrix lower than FICA_TOL are discarded for analysis. |
Definition of FastICA (Independent Component Analysis) for IT++.
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
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
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.