By Topic

Non-Cancellation Multistage Kurtosis Maximization with Prewhitening for Blind Source Separation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Xiang Chen ; Department of Electronic Engineering, Tsinghua University, Beijing ; Chong-Yung Chi ; Chon-Wa Wong ; Shidong Zhou
more authors

Chi et al. recently proposed two effective non-cancellation multistage (NCMS) blind source separation algorithms, one using the turbo source extraction algorithm (TSEA), called the NCMS-TSEA, and the other using the fast kurtosis maximization algorithm (FKMA), called the NCMS-FKMA. Their computational complexity and performance heavily depend on the dimension of multi-sensor data, i.e., number of sensors. This paper proposes the inclusion of the prewhitening processing in the NCMS-TSEA and NCMS-FKMA before performing source extraction. We come up with two improved algorithms with significant computational savings on one hand, and some performance improvements on the other hand (owing to dimension reduction and noise reduction by prewhitening processing), especially when the number of sensors is much larger than the number of sources. Simulation results are presented to verify the efficacy and computational efficiency of the proposed algorithms.

Published in:

2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers

Date of Conference:

4-7 Nov. 2007