Blind Extraction of Chaotic Signals by Using the Fast Independent Component Analysis Algorithm |
| |
Authors: | CHEN Hong-Bin FENG Jiu-Chao FANG Yong |
| |
Affiliation: | School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641School of Communication and Information Engineering, Shanghai University, Shanghai 200072 |
| |
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 definedas 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. |
| |
Keywords: | 05.45.-a 84.40.Ua |
本文献已被 维普 等数据库收录! |
| 点击此处可从《中国物理快报》浏览原始摘要信息 |
|
点击此处可从《中国物理快报》下载免费的PDF全文 |
|