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Two-stage series-based neural network approach to nonlinear independent component analysis

Lookup NU author(s): Dr Li Khor, Dr Wai Lok Woo, Professor Satnam Dlay

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Abstract

Linear Independent Component Analysis (ICA) played an important role in the development of various signal processing techniques due to the inherent simplicity. However, the assumption of linear mixture is always violated in real life, which narrows down its applications. In this paper, the problem of nonlinear independent component analysis is considered. Based on a new type of nonlinear mixing model, we propose a two-stage series-based approach to recover the original source signals. The two-stage series-based algorithm offers significant advantages in terms of reduced computational complexity and better learning dynamics of the trajectory. Simulations have also been carried out to verify the efficacy of the proposed method. © 2006 IEEE.


Publication metadata

Author(s): Gao P, Khor LC, Woo WL, Dlay SS

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Proceedings of the IEEE International Symposium on Circuits and Systems

Year of Conference: 2006

Pages: 4559-4562

ISSN: 0271-4302

Publisher: IEEE

URL: http://dx.doi.org/10.1109/ISCAS.2006.1693644

DOI: 10.1109/ISCAS.2006.1693644

Library holdings: Search Newcastle University Library for this item

ISBN: 0780393902


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