arrow
返回

Tracking analysis of augmented complex least mean square algorithm

delete2015-07-24
delete5
PRE
AI
A
Azam Khalili *
A
Amir Rastegarnia
DOI:10.1002/acs.2594delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
The augmented complex least mean-square (ACLMS) algorithm is a suitable algorithm for the processing of both second-order circular (proper) and noncircular (improper) signals. In this paper, we provide tracking analysis of the ACLMS algorithm in the non-stationary environments. Using the established energy conservation argument, we derive a variance relation that contains moments that represent the effects of non-stationary environment. We evaluate these moments and derive closed-form expressions for the excess mean-square error (EMSE) and mean-square error (MSE). The derived expressions, supported by simulations, reveal that unlike the stationary case, the steady-state EMSE, and MSE curves are not monotonically increasing functions of the step-size parameter. We also use this observation to optimize the step-size learning parameter. Simulation results illustrate the theoretical findings and match well with theory. Copyright (c) 2015 John Wiley & Sons, Ltd.
Keyword:
augmented CLMS
widely linear model
energy conservation
tracking
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

International Journal of Adaptive Control and Signal Processing 封面图
International Journal of Adaptive Control and Signal Processing
IF:
3.8
论文数:
2.6K
被引数:
3.6K

机构

暂无机构信息