A QR-based least mean squares algorithm for adaptive parameter estimation

被引：6
|
作者：
Liu, ZS [1 ]
Li, J [1 ]
机构：
[1] Univ Florida, Dept Elect & Comp Engn, Gainesville, FL 32611 USA
来源：
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-ANALOG AND DIGITAL SIGNAL PROCESSING | 1998年 / 45卷 / 03期
基金：
美国国家科学基金会;
关键词：
adaptive parameter estimation; convergence analysis; error propagation properties; LMS algorithms; QR-decomposition;
D O I：
10.1109/82.664238
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：
The optimum nonlinearly modified least-mean-square (ONM-LMS) algorithm has been shown to perform better than both the LMS and the normalized LMS algorithms. This paper proposes a QR-LMS adaptive parameter estimation algorithm that can perform significantly better than ONM-LMS. The performances of QR-LMS, including its numerical stability, error propagation property, and tracking ability, are analyzed. These properties are also verified with numerical examples.
引用
收藏
页码：321 / 329
页数：9
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