Steady-state performance of non-negative least-mean-square algorithm and its variants

Jie Chen; José Carlos M. Bermudez; Cédric Richard

doi:10.1109/LSP.2014.2320944

Steady-state performance of non-negative least-mean-square algorithm and its variants

Jie Chen
, José Carlos M. Bermudez
, Cédric Richard

Université de Nice Sophia-Antipolis
Universidade Federal de Santa Catarina

科研成果: 期刊稿件 › 文章 › 同行评审

26 引用（Scopus）

摘要

The Non-Negative Least-Mean-Square (NNLMS) algorithm and its variants have been proposed for online estimation under non-negativity constraints. The transient behavior of the NNLMS, Normalized NNLMS, Exponential NNLMS and Sign-Sign NNLMS algorithms have been studied in the literature. In this letter, we derive closed-form expressions for the steady-state excess mean-square error (EMSE) for the four algorithms. Simulation results illustrate the accuracy of the theoretical results. This work complements the understanding of the behavior of these algorithms.

源语言	英语
文章编号	6807652
页（从-至）	928-932
页数	5
期刊	IEEE Signal Processing Letters
卷	21
期	8
DOI	https://doi.org/10.1109/LSP.2014.2320944
出版状态	已出版 - 8月 2014
已对外发布	是

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abstract = "The Non-Negative Least-Mean-Square (NNLMS) algorithm and its variants have been proposed for online estimation under non-negativity constraints. The transient behavior of the NNLMS, Normalized NNLMS, Exponential NNLMS and Sign-Sign NNLMS algorithms have been studied in the literature. In this letter, we derive closed-form expressions for the steady-state excess mean-square error (EMSE) for the four algorithms. Simulation results illustrate the accuracy of the theoretical results. This work complements the understanding of the behavior of these algorithms.",

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AB - The Non-Negative Least-Mean-Square (NNLMS) algorithm and its variants have been proposed for online estimation under non-negativity constraints. The transient behavior of the NNLMS, Normalized NNLMS, Exponential NNLMS and Sign-Sign NNLMS algorithms have been studied in the literature. In this letter, we derive closed-form expressions for the steady-state excess mean-square error (EMSE) for the four algorithms. Simulation results illustrate the accuracy of the theoretical results. This work complements the understanding of the behavior of these algorithms.

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Steady-state performance of non-negative least-mean-square algorithm and its variants

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