DocumentCode :
2718484
Title :
Blind Separation of Mixing Chaotic Signals Based on ICA Using Kurtosis
Author :
Jianning, Yang ; Yi, Fang
Author_Institution :
Sch. of Electr. & Inf., Jiangsu Univ., Zhenjiang, China
fYear :
2012
fDate :
11-13 Aug. 2012
Firstpage :
903
Lastpage :
905
Abstract :
There are some methods that separate the mixing chaotic signals, but they have to use the internal properties of signals and special constraints. By exploiting the independence of sources in the mixing chaotic signals, the fixed-point ICA based on the kurtosis to separate the mixtures is used. It is accordance with the ICA (Independent Component Analysis) estimation principle of maximum nongaussianity. The results by computer simulation indicate that the mixed chaotic signals, by using the method, can be separated and get the sources signals fast and effectively.
Keywords :
blind source separation; chaos; independent component analysis; signal sources; blind separation; chaotic signal mixing; fixed-point ICA; independent component analysis estimation principle; kurtosis; signal sources; Chaotic communication; Equations; Logistics; Mathematical model; Matrix decomposition; Vectors; Blind Separation; Chaotic Signals; ICA;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science & Service System (CSSS), 2012 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-0721-5
Type :
conf
DOI :
10.1109/CSSS.2012.229
Filename :
6394467
Link To Document :
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