DocumentCode :
2706405
Title :
Geometry and Manifolds for Independent Component Analysis
Author :
Plumbley, Mark D.
Author_Institution :
Dept. of Electron. Eng., Queen Mary Univ. of London, UK
Volume :
4
fYear :
2007
fDate :
15-20 April 2007
Abstract :
In the last few years, there has been a great interest in the use of geometrical methods for independent component analysis (ICA), both to gain insight into the optimization process and to develop more efficient optimization algorithms. Much of this work involves concepts from differential geometry, such as Lie groups, Stiefel manifolds, or tangent planes that may be unfamiliar to signal processing researchers. The purpose of this tutorial paper is to introduce some of these geometry concepts to signal processing and ICA researchers, without assuming any existing background in differential geometry. The emphasis of the paper is on making the important concepts in this field accessible, rather than mathematical rigour.
Keywords :
geometry; independent component analysis; optimisation; signal processing; ICA; Lie groups; Stiefel manifolds; differential geometry; independent component analysis; optimization process; signal processing; Cost function; Covariance matrix; Geometry; Gradient methods; Independent component analysis; Length measurement; Manifolds; Optimization methods; Signal analysis; Signal processing algorithms; Geometry; Learning systems; Neural networks; Optimization methods; Signal analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Conference_Location :
Honolulu, HI
ISSN :
1520-6149
Print_ISBN :
1-4244-0727-3
Type :
conf
DOI :
10.1109/ICASSP.2007.367340
Filename :
4218371
Link To Document :
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