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The Euclidean Direction Search Algorithm in Adaptive Filtering
Tamal BOSE Guo-Fang XU
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2002/03/01
Print ISSN: 0916-8508
Type of Manuscript: INVITED PAPER (Special Section on the Trend of Digital Signal Processing and Its Future Direction)
adaptive filters, least squares, Euclidean direction search, channel equalizer, image restoration,
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A new class of least-squares algorithms is presented for adaptive filtering. The idea is to use a fixed set of directions and perform line search with one direction at a time in a cyclic fashion. These algorithms are called Euclidean Direction Search (EDS) algorithms. The fast version of this class is called the Fast-EDS or FEDS algorithm. It is shown to have O(N) computational complexity and a convergence rate comparable to that of the RLS algorithm. Computer simulations are presented to illustrate the performance of the new algorithm.