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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/849

Title: A Review of Independent Component Analysis Techniques and their Applications
Authors: Acharya, D P
Panda, G
Keywords: Blind source separation
Higher order statistics
Independent component analysis
Issue Date: 2008
Publisher: Medknow
Citation: IETE Technical Review, Volume 25, Issue 6, 1 November 2008, Pages 320-332
Abstract: Independent Component Analysis, a computationally efficient blind statistical signal processing technique, has been an area of interest for researchers for many practical applications in various fields of science and engineering. The present paper attempts to treat the fundamental concepts involved in the independent component analysis (ICA) technique and reviews different ICA algorithms. A thorough discussion of the algorithms with their merits and weaknesses has been carried out. Applications of the ICA algorithms in different fields of science and technology have been reviewed. The limitations and ambiguities of the ICA techniques developed so far have also been outlined. Though several articles have reviewed the ICA techniques in literature, they suffer from the limitation of not being comprehensive to a first time reader or not incorporating the latest available algorithm and their applications. In this work, we present different ICA algorithms from their basics to their potential...
Description: Copyright for the published paper belong to the publisher
URI: http://dx.doi.org/10.4103/0256-4602.45424
Appears in Collections:Conference Papers

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