Title :
Robust rank-EASI algorithm for blind source separation
Author :
Zhang, Y. ; Kassam, S.A.
Author_Institution :
Dept. of Electr. Eng., Univ. of Pennsylvania, Philadelphia, PA, USA
fDate :
2/1/2004 12:00:00 AM
Abstract :
Robustness against deviations from nominal source pdf assumptions is very desirable in blind source separation (BSS) algorithms. In the paper, a new approach for robust BSS is proposed. The EASI (equivariant adaptive separation by independence) algorithm (Cardoso and Laheld, 1996) is modified to use ranks of observed signals. The modified EASI algorithm can be applied to both real-valued and complex-valued data. Design guidelines are discussed for the nonlinear rank weighting functions in the modified EASI algorithm. Simulation results for two examples are given, showing very good performance.
Keywords :
adaptive signal processing; blind source separation; independent component analysis; probability; blind source separation; complex-valued data; equivariant adaptive separation by independence algorithm; nominal source PDF assumption; nonlinear rank weighting function; probability density function; real-valued data; robust rank algorithm;
Journal_Title :
Communications, IEE Proceedings-
DOI :
10.1049/ip-com:20040276