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Looping LMS versus fast least squares algorithms: who gets there first?

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4 Author(s)
Alberi, M.L. ; ETIS, Cergy-Pontoise, France ; Casas, R.A. ; Fijalkow, I. ; Johnson, C.R.

This paper analytically compares, in terms of the convergence time, fast least squares estimation algorithms for channel identification and equalization to looping LMS (LLMS), a scheme which repeatedly applies the least mean squares algorithm to a block of received data. In this study, the convergence time is defined as the actual time (in seconds) taken by an algorithm to reach a desired performance. The old theme on LMS and fast least squares algorithms convergence is revisited from a novel perspective: the comparison is made from a complexity viewpoint, which not only takes into account the statistical properties of studied algorithms but also the number of floating point operations

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Signal Processing Advances in Wireless Communications, 1999. SPAWC '99. 1999 2nd IEEE Workshop on

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