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A Recursive Data Least Square Algorithm and Its Channel Equalization Application
Jun-Seok LIM Jea-Soo KIM Koeng-Mo SUNG
IEICE TRANSACTIONS on Communications
Publication Date: 2007/08/01
Online ISSN: 1745-1345
Print ISSN: 0916-8516
Type of Manuscript: LETTER
Category: Fundamental Theories for Communications
data least squares method, generalized eigenvalue problem, equalization,
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Using the recursive generalized eigendecomposition method, we develop a recursive form solution to the data least squares (DLS) problem in which the error is assumed to lie in the data matrix only. We apply it to a linear channel equalizer. Simulations shows that the DLS-based equalizer outperforms the ordinary least squares-based one in a channel equalization problem.