On the mean-square performance of the constrained LMS algorithm
Date
2015
Authors
Arablouei, R.
Doğançay, K.
Werner, S.
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Journal article
Citation
Signal Processing, 2015; 117:192-197
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Abstract
The so-called constrained least mean-square algorithm is one of the most commonly used linear-equality-constrained adaptive filtering algorithms. Its main advantages are adaptability and relative simplicity. In order to gain analytical insights into the performance of this algorithm, we examine its mean-square performance and derive theoretical expressions for its transient and steady-state mean-square deviation. Our methodology is inspired by the principle of energy conservation in adaptive filters. Simulation results corroborate the accuracy of the derived formula.
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Link to a related website: http://arxiv.org/pdf/1412.2424, Open Access via Unpaywall
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Copyright 2015 Elsevier