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Blind Extraction of Chaotic Signals by Using the Fast Independent Component Analysis Algorithm |
| CHEN Hong-Bin1;FENG Jiu-Chao1;FANG Yong2 |
| 1School of Electronic and Information Engineering, South China University of Technology, Guangzhou 5106412School of Communication and Information Engineering, Shanghai University, Shanghai 200072 |
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| Cite this article: |
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CHEN Hong-Bin, FENG Jiu-Chao, FANG Yong 2008 Chin. Phys. Lett. 25 405-408 |
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Abstract We report the results of using the fast independent component analysis (FastICA) algorithm to realize blind extraction of chaotic signals. Two cases are taken into consideration: namely, the mixture is noiseless or contaminated by noise. Pre-whitening is employed to reduce the effect of noise before using the FastICA algorithm. The correlation coefficient criterion is adopted to evaluate the performance, and the success rate is defined
as a new criterion to indicate the performance with respect to noise or different mixing matrices. Simulation results show that the FastICA algorithm can extract the chaotic signals effectively. The impact of noise, the length of a signal frame, the number of sources and the number of observed mixtures on the performance is investigated in detail. It is also shown that regarding a noise as an independent source is not always correct.
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| Keywords:
05.45.-a
84.40.Ua
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Received: 17 September 2007
Published: 30 January 2008
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| PACS: |
05.45.-a
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(Nonlinear dynamics and chaos)
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84.40.Ua
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(Telecommunications: signal transmission and processing; communication satellites)
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