A new quasi switching algorithm for blind source separation

被引：0

作者：

Si, Xi-Cai ^{[1
]}

Chai, Juan-Fang ^{[1
]}

Zhang, Wen-Wen ^{[1
]}

Li, Li ^{[1
]}

机构：

[1] College of Information and Communication Engineering, Harbin Engineering University

来源：

Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University | 2009年 / 30卷 / 06期

关键词：

Activation function; Blind source separation; Kurtosis; Multi-source separation; Quasi switching algorithm;

D O I：

10.369/j.issn.1006-7043.2009.06.021

中图分类号：

学科分类号：

摘要：

A new quasi switching algorithm for blind source separation (BSS) was developed that resolves difficulties in the separation of all kinds of seriously mixed signals in an electronic warfare (EW) environment. The algorithm first introduces a unit symmetrical sliding weighted vector to weight estimated signals after iteration as source signals. It uses signal kurtosis to replace a symbol bit for kurtosis as a judging function to adaptively choose and weight the corresponding activation function. This gives a new judging method which was used to judge the finishing time of iteration in signal sorting. Computer simulation results showed that, under the influence of strong background noise, the novel algorithm can be more effective in unknown multi-source separation of linear mixed signals than the original algorithm. In addition, separation efficiency, stability, process capacity and anti-noise performance were greatly improved relative to the original algorithm.

引用

页码：703 / 707

页数：4

共 10 条

[1]

Comon P., Independent component analysis, A New Concept Signal Processing, 36, 3, pp. 287-314, (1994)

[2]

Bell A.J., Sejnowski T.J., An information maximization approach to blind separation and blind deconvolution, Neural Computation, 7, 6, pp. 1004-1159, (1995)

[3]

Lee T.W., Independent component analysis using an extended infomax algorithm for mixed sub-Gaussian and super-Gaussian sources, Neural Computation, 11, 2, pp. 409-433, (1999)

[4]

Niu L., A new switching algorithm of blind source separation based on kurtosis, Journal of System Simulation, 17, 1, pp. 185-188, (2005)

[5]

Sun Z., A new kurtosis loose switching algorithms for blind source separation, Journal of Hangzhou Dianzi University, 27, 1, pp. 33-37, (2007)

[6]

pp. 36-39, (2006)

[7]

Amri S., Cichocki A., Adaptive blind signal processing-neural network approaches, Proceedings of the IEEE, 86, 10, pp. 2026-2046, (1998)

[8]

pp. 327-361, (2003)

[9]

Cardoso A.S., Blind source separation-semi-parametric statistical approach, IEEE Trans on Signal Processing, 45, 11, pp. 2692-2700, (1997)

[10]

pp. 247-286, (2006)

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