Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Fixed-Point Algorithms for the Blind Separation of Arbitrary Complex-Valued Non-Gaussian Signal Mixtures | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2007 Article ID 36525 15 pages doi 2007 36525 Research Article Fixed-Point Algorithms for the Blind Separation of Arbitrary Complex-Valued Non-Gaussian Signal Mixtures Scott C. Douglas Department of Electrical Engineering School of Engineering Southern Methodist University . Box 750338 Dallas newline tX 75275 UsA Received 1 October 2005 Revised 10 May 2006 Accepted 22 June 2006 Recommended by Andrzej Cichocki We derive new fixed-point algorithms for the blind separation of complex-valued mixtures of independent noncircularly symmetric and non-Gaussian source signals. Leveraging recently developed results on the separability of complex-valued signal mixtures we systematically construct iterative procedures on a kurtosis-based contrast whose evolutionary characteristics are identical to those of the FastICA algorithm of Hyvarinen and Oja in the real-valued mixture case. Thus our methods inherit the fast convergence properties computational simplicity and ease of use of the FastICA algorithm while at the same time extending this class of techniques to complex signal mixtures. For extracting multiple sources symmetric and asymmetric signal deflation procedures can be employed. Simulations for both noiseless and noisy mixtures indicate that the proposed algorithms have superior finite-sample performance in data-starved scenarios as compared to existing complex ICA methods while performing about as well as the best of these techniques for larger data-record lengths. Copyright 2007 Hindawi Publishing Corporation. All rights reserved. 1. INTRODUCTION Both blind source separation BSS and independent component analysis ICA are concerned with m-dimensional linear signal mixtures of the form x k As k 1 where A is an unknown m X m mixing matrix and s k S1 k Sm k T is a vector-valued signal of sources. In most treatments of either task in the scientific literature the sources Sj k .
