Title :
Turbo source separation algorithm using HOS based inverse filter criteria
Author :
Chi, Chong-Yung ; Chen, Chun-Jen ; Wang, Faa-Yeu ; Chen, Ching-Yung ; Peng, Chun-Hsien
Author_Institution :
Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan
Abstract :
Ding and Ngugen proposed a kurtosis maximization algorithm and Chi arid Chen proposed a fast kurtosis maximization algorithm (FKMA) for blind separation of a instantaneous mixture of colored non-Gaussian sources. Their algorithms only involve spatial processing, but their performance may significantly degrade for finite signal-to-noise ratio as kurtosis magnitudes of source signals are not sufficiently large. This paper proposes a novel iterative blind source separation algorithm, called a turbo source separation algorithm (TSSA), which alternatively involves spatial processing as the FKMA, and temporal processing (blind deconvolution) using Chi and Cheri´s fast inverse filter criteria algorithm at each iteration. Some simulation results are presented to support that the proposed TSSA works well with better performance than the FKMA and some existing second-order statistics based algorithms.
Keywords :
blind source separation; deconvolution; higher order statistics; iterative methods; optimisation; blind deconvolution; blind separation; colored nonGaussian sources; fast kurtosis maximization algorithm; higher order statistics; inverse filter criteria; iterative blind source separation algorithm; kurtosis maximization algorithm; second-order statistics based algorithms; signal-to-noise ratio; spatial processing; temporal processing; turbo source separation; Blind source separation; Degradation; Filters; Iterative algorithms; Sensor arrays; Signal processing; Signal processing algorithms; Signal to noise ratio; Source separation; Statistics;
Conference_Titel :
Signal Processing and Information Technology, 2003. ISSPIT 2003. Proceedings of the 3rd IEEE International Symposium on
Print_ISBN :
0-7803-8292-7
DOI :
10.1109/ISSPIT.2003.1341167