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Blind Extraction of Chaotic Signals by Using the Fast Independent Component Analysis Algorithm 被引量:7
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作者 陈宏滨 冯久超 方勇 《Chinese Physics Letters》 SCIE CAS CSCD 2008年第2期405-408,共4页
We report the results of using the fast independent component analysis (FastICA) algorithm to realize Mind extraction of chaotic signals. Two cases are taken into consideration: namely, the mixture is noiseless or ... We report the results of using the fast independent component analysis (FastICA) algorithm to realize Mind 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. 展开更多
关键词 instantaneous mixtureS SEPARATION NOISE
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