DocumentCode :
527653
Title :
Application of immune clonal algorithm and mutual information in nonlinear blind source separation
Author :
Wu, Xinjie ; Xu, Chao ; Fu, Rongrong ; Wu, Chengdong
Author_Institution :
Coll. of Phys., Liaoning Univ., Shenyang, China
Volume :
6
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
2847
Lastpage :
2851
Abstract :
In nonlinear blind source separation (NBSS), usually it is very difficulty to find the global optimal solutions of cost functions due to the existence of many local optimal solutions. In order to overcome the disadvantage mentioned above, a NBSS algorithm based on immune clonal algorithm is proposed in this paper. The odd polynomial function of high-order is used to fit the nonlinear mixed function in this method; the mutual information of separation signals is used as cost function of immune clonal algorithm. In simulation experiment, nonlinear mixed signals are successfully separated by this method. The similar coefficients of separation signals obtained by this algorithm and source signals are higher than 98%. The simulation experiment results have shown that this method can well solve the problem of NBSS.
Keywords :
blind source separation; nonlinear functions; polynomials; global optimal solutions; immune clonal algorithm; local optimal solutions; mutual information; nonlinear blind source separation; nonlinear mixed function; nonlinear mixed signals; odd polynomial function; Blind source separation; Immune system; Mathematical model; Mutual information; Polynomials; Signal processing algorithms; blind source separation; immune clonal algorithm; mutual information; nonlinear mixture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
Type :
conf
DOI :
10.1109/ICNC.2010.5583525
Filename :
5583525
Link To Document :
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