Normalised least-mean-square algorithm for adaptive filtering of impulsive measurement noises and noisy inputs

被引：57
|
作者：
Jung, Sang Mok [1 ]
Park, PooGyeon [1 ]
机构：
[1] Pohang Univ Sci & Technol, Dept Elect Engn, Pohang, Gyungbuk, South Korea
来源：
ELECTRONICS LETTERS | 2013年 / 49卷 / 20期
基金：
新加坡国家研究基金会;
关键词：
Estimation methods - Input noise - Measurement Noise - Normalised least mean square algorithms;
D O I：
10.1049/el.2013.2482
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：
A bias-compensated error-modified normalised least-mean-square algorithm is proposed. The proposed algorithm employs nonlinearity to improve robustness against impulsive measurement noise, and introduces an unbiasedness criterion to eliminate the bias due to noisy inputs in an impulsive measurement noise environment. To eliminate the bias properly, a new estimation method for the input noise variance is also derived. Simulations in a system identification context show that the proposed algorithm outperforms the other algorithms because of the improved adaptability to impulsive measurement noise and input noise in the system. © The Institution of Engineering and Technology 2013.
引用
收藏
页码：1270 / 1271
页数：2
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