Blind Source Separation Based on Genetic Algorithm

Yi Yeqing; Lin Yaping; Lin Mu; Li Xiaolong; Wang Lei

Journal of Computer Research and Development > 2006 > 43(2): 244-252.

Yi Yeqing, Lin Yaping, Lin Mu, Li Xiaolong, Wang Lei. Blind Source Separation Based on Genetic Algorithm[J]. Journal of Computer Research and Development, 2006, 43(2): 244-252.

Citation:

Yi Yeqing, Lin Yaping, Lin Mu, Li Xiaolong, Wang Lei. Blind Source Separation Based on Genetic Algorithm[J]. Journal of Computer Research and Development, 2006, 43(2): 244-252.

Citation:

Yi Yeqing, Lin Yaping, Lin Mu, Li Xiaolong, Wang Lei. Blind Source Separation Based on Genetic Algorithm[J]. Journal of Computer Research and Development, 2006, 43(2): 244-252.

PDF (557 KB)

Blind Source Separation Based on Genetic Algorithm

1(College of Software, Hunan University, Changsha 410082)2(College of Mathematics and Econometrics, Hunan University, Changsha 410082)3(College of Computer and Communication, Hunan University, Changsha 410082)

More Information

Published Date: February 14, 2006

Graphical Abstract

Abstract

Abstract

Recovering the unobserved source signals from their mixtures is a typical problem in array processing and data analysis. Independent component analysis (ICA) is a new and powerful method to solve this problem. JADE (joint approximate decomposition of eigen matrices) based on 4th-order cumulants is a common approach for ICA. However, it can only get approximate solution when k＞2 and the results are not accurate. In this paper, a blind source separation based on genetic algorithm is proposed. The analysis and simulations suggest that the scheme is feasible and effective.
- blind source separation,
- joint diagonalization,
- independent component analysis,
- genetic algorithm

FullText(HTML)

References (0)

[1]	Gao Zhanzhan, Tang Guangming, Wang Shuo. A Novel VoIP Steganography Method Based on Bayesian Network and Matrix Embedding[J]. Journal of Computer Research and Development, 2018, 55(4): 854-863. DOI: 10.7544/issn1000-1239.2018.20161042
[2]	Wang Liang, Wang Weiping, Meng Dan. Privacy Preserving Data Publishing via Weighted Bayesian Networks[J]. Journal of Computer Research and Development, 2016, 53(10): 2343-2353. DOI: 10.7544/issn1000-1239.2016.20160465
[3]	Shu Jian, Tang Jin, Liu Linlan, Hu Gang, Liu Song. Fuzzy Support Vector Regression-Based Link Quality Prediction Model for Wireless Sensor Networks[J]. Journal of Computer Research and Development, 2015, 52(8): 1842-1851. DOI: 10.7544/issn1000-1239.2015.20140670
[4]	Si Guannan, Ren Yuhan, Xu Jing, and Yang Jufeng. A Dependability Evaluation Model for Internetware Based on Bayesian Network[J]. Journal of Computer Research and Development, 2012, 49(5): 1028-1038.
[5]	Qian Ning, Wu Guoxin, and Zhao Shenghui. A Bayesian Network-Based Search Method in Unstructured Peer-to-Peer Networks[J]. Journal of Computer Research and Development, 2009, 46(6): 889-897.
[6]	Wang Shuangcheng, Leng Cuiping, Cao Feng. Revising the Parameters of Bayesian Network with Multi-Father Nodes from Small Data Set[J]. Journal of Computer Research and Development, 2009, 46(5): 787-793.
[7]	Miao Duoqian, Wang Ruizhi, and Ran Wei. A Dynamic Bayesian Network Based Framework for Continuous Speech Recognition and its Token Passing Model[J]. Journal of Computer Research and Development, 2008, 45(11): 1882-1891.
[8]	Ji Junzhong, Liu Chunnian, and Yan Jing. A Fast Bayesian Network Structure Learning Algorithm[J]. Journal of Computer Research and Development, 2007, 44(3).
[9]	Wu Zhiyong and Cai Lianhong. Audio-Visual Bimodal Speaker Identification Using Dynamic Bayesian Networks[J]. Journal of Computer Research and Development, 2006, 43(3): 470-475.
[10]	Wang Fei, Liu Dayou, Wang Songxin. Research on Incremental Learning of Bayesian Network Structure Based on Genetic Algorithms[J]. Journal of Computer Research and Development, 2005, 42(9): 1461-1466.