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Abstract and Applied Analysis
Volume 2015 (2015), Article ID 386201, 8 pages
Research Article

Independent Component Analysis Based on Information Bottleneck

1School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an 710049, China
2Department of Mathematics and Statistics, University of Victoria, Victoria, BC, Canada V8W 3R4
3School of Computer Science and Engineering, Xi’an University of Technology, Shaanxi Key Laboratory for Network Computing and Security Technology, Xi’an 710048, China
4Department of Construction and Information Engineering, Guangxi Modern Vocational Technology College, Hechi, Guangxi 547000, China

Received 26 June 2014; Accepted 15 July 2014

Academic Editor: Hui Zhang

Copyright © 2015 Qiao Ke 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 paper is mainly used to provide the equivalence of two algorithms of independent component analysis (ICA) based on the information bottleneck (IB). In the viewpoint of information theory, we attempt to explain the two classical algorithms of ICA by information bottleneck. Furthermore, via the numerical experiments with the synthetic data, sonic data, and image, ICA is proved to be an edificatory way to solve BSS successfully relying on the information theory. Finally, two realistic numerical experiments are conducted via FastICA in order to illustrate the efficiency and practicality of the algorithm as well as the drawbacks in the process of the recovery images the mixing images.