Mean Weight Behavior of the NLMS Algorithm for Correlated Gaussian Inputs

被引：10

作者：

Al-Naffouri, Tareq Y. ^{[1
]}

Moinuddin, Muhammad ^{[2
]}

Sohail, Muhammad S. ^{[1
]}

机构：

[1] King Fahd Univ Petr & Minerals, Dept Elect Engn, Dhahran 31261, Saudi Arabia

[2] Iqra Univ, Telecommun Engn Dept, Karachi, Pakistan

来源：

IEEE SIGNAL PROCESSING LETTERS | 2011年 / 18卷 / 01期

关键词：

Adaptive algorithms; indefinite quadratic forms; mean behavior; spherically symmetric random variables; PERFORMANCE ANALYSIS; LMS; CONVERGENCE;

D O I：

10.1109/LSP.2010.2090142

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This letter presents a novel approach for evaluating the mean behavior of the well known normalized least mean squares (NLMS) adaptive algorithm for a circularly correlated Gaussian input. The mean analysis of the NLMS algorithm requires the calculation of some normalized moments of the input. This is done by first expressing these moments in terms of ratios of quadratic forms of spherically symmetric random variables and finding the cumulative density function (CDF) of these variables. The CDF is then used to calculate the required moments. As a result, we obtain explicit expressions for the mean behavior of the NLMS algorithm.

引用

页码：7 / 10

页数：4

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