Blind Source Separation Based on Covariance Ratio and Artificial Bee Colony Algorithm
Joint Authors
Chen, Lei
Liang, Jingyi
Zhang, Liyi
Huang, Yong
Guo, Yanju
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-02
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Chen, Lei& Zhang, Liyi& Guo, Yanju& Huang, Yong& Liang, Jingyi. 2014. Blind Source Separation Based on Covariance Ratio and Artificial Bee Colony Algorithm. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-475284
Modern Language Association (MLA)
Chen, Lei…[et al.]. Blind Source Separation Based on Covariance Ratio and Artificial Bee Colony Algorithm. Mathematical Problems in Engineering No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-475284
American Medical Association (AMA)
Chen, Lei& Zhang, Liyi& Guo, Yanju& Huang, Yong& Liang, Jingyi. Blind Source Separation Based on Covariance Ratio and Artificial Bee Colony Algorithm. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-475284
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-475284