带自适应动量因子的变步长盲源分离方法

doi:10.11959/j.issn.1000-436x.2017067

Abstract

Abstract:

A variable-step blind source separation algorithm based on the natural gradient with adaptive momentum factor was proposed,which could cope with the determined blind source separation in the environment of stationary and non-stationary.Function estimation mixed matrix was constructed by performance index.The estimated performance index was obtained by the estimated mixed matrix,and the constructor was updated by the estimated performance index.Then,the constructor was plugged with appropriate experienced parameter into the proposed algorithm and step and momentum factor was adaptively adjusted.Finally,the estimation source signals could be obtained.Simulations show that the proposed algorithm is effective to estimate the mixed matrix in the stationary and non-stationary environments,and the proposed algorithm has faster convergence speed and lower steady error as well as separates source signals effectively.

Key words: blind source separation, natural gradient, momentum factor, variable-step

CLC Number:

TN911.6

Tian-qi ZHANG,Bao-ze MA,Xing-zi QIANG,Sheng-rong QUAN. Variable-step blind source separation method with adaptive momentum factor[J]. Journal on Communications, 2017, 38(3): 16-24.

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算法		Chebysev序列长度			Henon序列长度			Logistic序列长度
算法	500	1 000	1 500	500	1 000	1 500	500	1 000	15 00
FastICA	0.783 5	0.763 5	0.761 3	0.925 8	0.936 8	0.932 1	0.663 6	0.705 5	0.690 7
EASI	0.815 7	0.934 3	0.980 1	0.726 5	0.876 7	0.976 5	0.912 1	0.968 6	0.996 8
VS-M-NGA	0.985 1	0.996 2	0.998 5	0.952 0	0.997 0	0.996 0	0.994 9	0.998 4	0.999 5

算法	Lorentz	Rossler	色噪声
FastICA	0.779 9	0.758 2	0.688 4
EASI	0.943 5	0.951 5	0.919 3
VS-M-NGA	0.966 7	0.950 9	0.996 8

Variable-step blind source separation method with adaptive momentum factor

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