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An Optimized Differential Step-Size LMS Algorithm

1
Department of Telecommunications, University Politehnica of Bucharest, 1-3, Iuliu Maniu Blvd., 061071 Bucharest, Romania
2
Department of Research and Development, Rohde & Schwarz Topex, 014142 Bucharest, Romania
3
INRS-EMT, University of Quebec, Montreal, QC H5A 1K6, Canada
*
Author to whom correspondence should be addressed.
Algorithms 2019, 12(8), 147; https://doi.org/10.3390/a12080147
Received: 28 June 2019 / Revised: 17 July 2019 / Accepted: 21 July 2019 / Published: 24 July 2019
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Abstract

Adaptive algorithms with differential step-sizes (related to the filter coefficients) are well known in the literature, most frequently as “proportionate” algorithms. Usually, they are derived on a heuristic basis. In this paper, we introduce an algorithm resulting from an optimization criterion. Thereby, we obtain a benchmark algorithm and also another version with lower computational complexity, which is rigorously valid for less correlated input signals. Simulation results confirm the theory and outline the performance of the algorithms. Unfortunately, the good performance is obtained by an important increase in computational complexity. Nevertheless, the proposed algorithms could represent useful benchmarks in the field. View Full-Text
Keywords: adaptive filter; least-mean-square (LMS) algorithm; optimized differential step-size LMS algorithm; system identification; echo cancellation adaptive filter; least-mean-square (LMS) algorithm; optimized differential step-size LMS algorithm; system identification; echo cancellation
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Rusu, A.-G.; Ciochină, S.; Paleologu, C.; Benesty, J. An Optimized Differential Step-Size LMS Algorithm. Algorithms 2019, 12, 147.

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