ICALAB Toolboxes

 

ICALAB for Signal Processing and ICALAB for Image Processing are two independent demo packages for MATLAB that implement a number of efficient algorithms for ICA (independent component analysis) employing HOS (higher order statistics), BSS (blind source separation) employing SOS (second order statistics) and LP (linear prediction), and BSE (blind signal extraction) employing various SOS and HOS methods.


The ICALAB Toolbox for signal Processing has been developed and designed by:

Andrzej Cichocki, Shun-ichi Amari, Krzysztof Siwek, Toshihisa Tanaka,

Anh Huy Phan, Rafal Zdunek, Sergio Cruces,

Pando Georgiev, Yoshikazu Washizawa, Zbigniew Leonowicz, Hovagim Bakardjian, Tomasz Rutkowski, Seungjin Choi, Adel Belouchrani, Allan Barros, Ruck Thawonmas, Tetsuya Hoya, Wakako Hashimoto, Yasushi Terazono in cooperation with other members of the Laboratory for Advanced Brain Signal Processing.

The graphic design, data visualization, user interface, extensive testing and integration of new ICA algorithms and the MC analysis for ICALAB Version 3 have been implemented in MATLAB® by

Anh Huy Phan and Andrzej Cichocki,

with cooperation of many researchers world-wide, especially:

Petr Tichavsky, Zbynek Koldovsky, Xi-Lin Li, Shuxue Ding, Zhi-Lin Zhang, Jonathon Chambers

The current version 3, as of March 28, 2007 includes only ICA and Second Order Statistics (SOS) Blind Sources Separation (BSS) algorithms. In the near future we plan to include other kind of algorithms such as SCA, MCA, NTC, NMF for both over-determined and underdetermined (over-complete) cases.

 

 

The ICALAB packages run on MATLAB 7.0 or higher. MATLAB is a registered trademark of The MathWorks, Inc.

 

ICALAB for Signal Processing

ICALAB for Image Processing

on-line help

on-line help

download page (ver. 3)

download page (ver. 2.0)

sample benchmarks

sample benchmarks

NEW! FAQ, Tips & Tricks

Help/manualICALAB-3.pdf

DISCLAIMER:

NEITHER THE AUTHORS NOR THEIR EMPLOYERS ACCEPT ANY RESPONSIBILITY OR LIABILITY FOR LOSS OR DAMAGE OCCASIONED TO ANY PERSON OR PROPERTY THROUGH USING SOFTWARE, MATERIALS, INSTRUCTIONS, METHODS OR IDEAS CONTAINED HEREIN, OR ACTING OR REFRAINING FROM ACTING AS A RESULT OF SUCH USE. THE AUTHORS EXPRESSLY DISCLAIM ALL IMPLIED WARRANTIES, INCLUDING MERCHANTABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE. THERE WILL BE NO DUTY ON THE AUTHORS TO CORRECT ANY ERRORS OR DEFECTS IN THE SOFTWARE. THIS SOFTWARE AND THE DOCUMENTATIONS ARE THE PROPERTY OF THE AUTHORS AND SHOULD ONLY BE USED FOR SCIENTIFIC AND EDUCATIONAL PURPOSES. ALL SOFTWARE IS PROVIDED FREE AND IT IS NOT SUPPORTED. THE AUTHORS ARE, HOWEVER, HAPPY TO RECEIVE COMMENTS, CRITICISM AND SUGGESTIONS ADDRESSED TO .

For information about the algorithms, see the above on-line helps and the book.

How to cite ICALAB

Please use the following citation formats:

1.      A. Cichocki, S. Amari, K. Siwek, T. Tanaka , Anh Huy Phan et al., ICALAB Toolboxes, http://www.bsp.brain.riken.jp/ICALAB.

2.      A. Cichocki, S. Amari, Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications, Wiley, 2003.


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