A Novel Evolutionary Approach for Blind Source Separation Based on Stones Method

摘要：

　　In recent years,much research emerged to modify Stones BSS method for solving a blind source separation problem; Stones method used to recover original signals from the mixture.In this work,new direction has been opened to use an intelligent soft computing technique (Fast Genetic Algorithm) with the temporal predictability of signals based on Stones BSS method.Proposed algorithm has been compared with well-known BSS algorithms (JADE,FICA,and Stones BSS) over super-Gaussian,sub-Gaussian,and Gaussian signals with linear mixture combination.Then eight voices have mixed randomly; and the proposed approach has successfully recovered the voices with high efficiency.Interpretation based on the responses of two different linear scalar filters to the same set of signals,whichindicate to Short-term and Long-term linear predictors with tuned Half-life values (hL,hs) genetically is a powerful new technique for solving BSS problem.In addition to the benefits of the Stones method,the proposed algorithm overcomes the local minima problem by successfully jump out of the potential local minimum.Usually recovery methods depend on the difference between signals and mixture proprieties; generally,there are three famous properties for any signal:(1) Gaussian probability density function based on the central limit theorem (2) Degree of statistical independence (3) Temporal predictability.So (1&2) proprieties,have previously been used as a base for separation but in this work only 3rd property has been used.In order to check the effectiveness of the proposed algorithm two performance indexes are used:Interference to signal ratio (ISR),and Integral square error (ISE).

关键词： blind signal separation signal temporal predictability fast genetic algorithms Stones BSS

作者: Abdullah Ahmed Zhang Chao Zhu Cang Yan

作者单位: College of Information and Communication Engineering, Harbin Engineering University, Harbin, China

会议类型: 国际会议

会议名称: 2012 IEEE 11th International Conference on Signal Processing (第11届IEEE信号处理国际会议)

会议地点: 北京

会议语种:英文

页码: 324-328

在线出版日期: 2012-10-21（万方平台首次上网日期，不代表论文的发表时间）