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An efficient equivariant adaptive separation via independence algorithm for acoustical source separation and identification 被引量:2
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作者 CHENG Wei LU Jian Tao +1 位作者 GAO Lin ZHANG Jie 《Science China(Technological Sciences)》 SCIE EI CAS CSCD 2016年第12期1825-1836,共12页
To balance the convergence rate and steadystate error of blind source separation(BSS) algorithms, an efficient equivariant adaptive separation via independence(Efficient EASI) algorithm is proposed based on separating... To balance the convergence rate and steadystate error of blind source separation(BSS) algorithms, an efficient equivariant adaptive separation via independence(Efficient EASI) algorithm is proposed based on separating indicator, which was derived from the convergence condition of EASI, and can be used to evaluate the separation degree of separated signals. Furthermore, a nonlinear monotone increasing function between suitable step sizes and separating indicator is constructed to adaptively adjust step sizes, and forgetting factor is employed to weaken effects of data at the initial stage. Numerical case studies and experimental studies on a test bed with shell structures are provided to validate the efficiency improvement of the proposed method. This study can benefit for vibration & acoustic monitoring and control, and machinery condition monitoring and fault diagnosis. 展开更多
关键词 equivariant adaptive separation via independence adaptive step size separation indicator forgetting factor acoustical source separation and identification
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