NDLI: Robust maximum signal fraction analysis for blind source separation

Content Provider	IET Digital Library
Author	Lu, Xuesong Li, Xiaomeng Fu, Mao sheng Wang, Haixian
Abstract	Blind source separation (BSS) is an active research topic in the fields of biomedical signal processing and brain–computer interface. As a representative technique, maximum signal fraction analysis (MSFA) has been recently developed for the problem of BSS. However, MSFA is formulated based on the L2-norm, and thus is prone to be negatively affected by outliers. In this study, the authors propose a robust alternative to MSFA based on the L1-norm, termed as MSFA-L1. Specifically, they re-define the objective function of MSFA, in which the energy quantities of both the signal and the noise are defined with the L1-norm rather than the L2-norm. By adopting the L1-norm, MSFA-L1 alleviates the negative influence of large deviations that are usually associated with outliers. Computationally, they design an iterative algorithm to optimise the objective function of MSFA-L1. The iterative procedure is shown to converge under the framework of bound optimisation. Experimental results on both synthetic data and real biomedical data demonstrate the effectiveness of the proposed MSFA-L1 approach.
Starting Page	969
Ending Page	974
Page Count	6
ISSN	17519675
Volume Number	11
e-ISSN	17519683
Issue Number	Issue 8, Oct (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/11/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2016.0529
Journal	IET Signal Processing
Publisher Date	2017-07-06
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Active Research Topic Biology And Medical Computing Biomedical Engineering Biomedical Measurement And Imaging Biomedical Signal Processing Blind Source Separation Bound Optimisation Brain-computer Interface Brain-computer Interfaces BSS Digital Signal Processing Interactive-Input Device Interpolation And Function Approximation Iterative Algorithm Iterative Method Iterative Procedure Maximum Signal Fraction Analysis Medical Signal Processing MSFA Numerical Analysis Numerical Approximation And Analysis Optimisation Optimisation Technique Real Biomedical Data Representative Technique Robust Maximum Signal Fraction Analysis Signal Processing And Detection User InterFace
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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