On the Mean-Square Performance of the Constrained LMS Algorithm
Systems and Control
2015-02-26 v2
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.
Cite
@article{arxiv.1412.2424,
title = {On the Mean-Square Performance of the Constrained LMS Algorithm},
author = {Reza Arablouei and Kutluyıl Doğançay and Stefan Werner},
journal= {arXiv preprint arXiv:1412.2424},
year = {2015}
}