Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2014, Article ID 484327, 12 pages
Research Article

Blind Source Separation Based on Covariance Ratio and Artificial Bee Colony Algorithm

1School of Information Engineering, Tianjin University of Commerce, Tianjin 300134, China
2School of Electronic Information Engineering, Tianjin University, Tianjin 300072, China
3School of Information Engineering, Hebei University of Technology, Tianjin 300401, China

Received 19 November 2013; Revised 8 May 2014; Accepted 9 May 2014; Published 2 June 2014

Academic Editor: Dan Simon

Copyright © 2014 Lei Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The computation amount in blind source separation based on bioinspired intelligence optimization is high. In order to solve this problem, we propose an effective blind source separation algorithm based on the artificial bee colony algorithm. In the proposed algorithm, the covariance ratio of the signals is utilized as the objective function and the artificial bee colony algorithm is used to solve it. The source signal component which is separated out, is then wiped off from mixtures using the deflation method. All the source signals can be recovered successfully by repeating the separation process. Simulation experiments demonstrate that significant improvement of the computation amount and the quality of signal separation is achieved by the proposed algorithm when compared to previous algorithms.