Constrained independent component analysis techniques

Constrained independent component analysis techniques

Independent component analysis (ICA) is a promising statistical signal processing technique. To overcome the inherent drawbacks encountered in the conventional ICA method, a general framework of constrained ICA is introduced. The prior knowledge of reference is incorporated into a negentropy based o...

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Bibliographic Details
Published in:2014 IEEE Workshop on Electronics, Computer and Applications pp. 419 - 422
Main Authors: Yongjian Zhao, Xiaoming Kong, Haining Jiang, Meixia Qu
Format: Conference Proceeding
Language:English
Published: IEEE 01-05-2014
Subjects:
Analysis
Biomedical measurement
Matrix
Optimization
Principal component analysis
Source
World Wide Web
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Summary:Independent component analysis (ICA) is a promising statistical signal processing technique. To overcome the inherent drawbacks encountered in the conventional ICA method, a general framework of constrained ICA is introduced. The prior knowledge of reference is incorporated into a negentropy based objective function so as to construct a constrained ICA problem. Subsequently, a flexible constrained ICA algorithm is derived for extraction of one or a few desired source signals. The utility of the proposed algorithm is demonstrated by computer simulations on real ECG data.
DOI:10.1109/IWECA.2014.6845646