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A New Method of Blind Source Separation Using Single-Channel ICA Based on Higher-Order Statistics
Joint Authors
Lu, Guangkuo
Xiao, Manlin
Wei, Ping
Zhang, Huaguo
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-08-11
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Methods of utilizing independent component analysis (ICA) give little guidance about practical considerations for separating single-channel real-world data, in which most of them are nonlinear, nonstationary, and even chaotic in many fields.
To solve this problem, a three-step method is provided in this paper.
In the first step, the measured signal which is assumed to be piecewise higher order stationary time series is introduced and divided into a series of higher order stationary segments by applying a modified segmentation algorithm.
Then the state space is reconstructed and the single-channel signal is transformed into a pseudo multiple input multiple output (MIMO) mode using a method of nonlinear analysis based on the high order statistics (HOS).
In the last step, ICA is performed on the pseudo MIMO data to decompose the single channel recording into its underlying independent components (ICs) and the interested ICs are then extracted.
Finally, the effectiveness and excellence of the higher order single-channel ICA (SCICA) method are validated with measured data throughout experiments.
Also, the proposed method in this paper is proved to be more robust under different SNR and/or embedding dimension via explicit formulae and simulations.
American Psychological Association (APA)
Lu, Guangkuo& Xiao, Manlin& Wei, Ping& Zhang, Huaguo. 2015. A New Method of Blind Source Separation Using Single-Channel ICA Based on Higher-Order Statistics. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1073848
Modern Language Association (MLA)
Lu, Guangkuo…[et al.]. A New Method of Blind Source Separation Using Single-Channel ICA Based on Higher-Order Statistics. Mathematical Problems in Engineering No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1073848
American Medical Association (AMA)
Lu, Guangkuo& Xiao, Manlin& Wei, Ping& Zhang, Huaguo. A New Method of Blind Source Separation Using Single-Channel ICA Based on Higher-Order Statistics. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1073848
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073848