NDLI: ICA based Noise Subtraction for Linear System Identification in Additive Noisy Output

Content Provider	IEEE Xplore Digital Library
Author	Ying Gao Yue Li Baojun Yang
Copyright Year	2007
Description	Author affiliation: Jilin Univ., Changchun (Ying Gao)
Abstract	This paper presents a new paradigm for linear system identification with additive noisy output and finds a powerful noise cancellation method. This method treats the model of system identification as an ICA problem with source signals received by several observed signals so that the estimate of noise can be obtained from the observed signals and then reduced from the noisy output by using an easy subtraction. This method does not rely on the statistic characteristics of the additive noise and can work well under low SNR conditions. Moreover, it settles the two ambiguities of the separated noise that are inherent in ICA by using some special characters of the mixing matrix. Synthetic data are applied to validate the effectiveness of the proposed method, and improved performance is obtained.
Starting Page	225
Ending Page	228
File Size	361273
Page Count	4
File Format	PDF
ISBN	9780769529097
DOI	10.1109/SNPD.2007.102
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-07-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Additive noise Linear systems Noise reduction Independent component analysis Signal processing Noise cancellation System identification Power system modeling Statistics Signal to noise ratio
Content Type	Text
Resource Type	Article

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