.png){kind=icon}
返回
A noise resilient variable step-size LMS algorithm
.png){kind=icon}
PRE
AI
DOI：10.1016/j.sigpro.2007.09.015.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This work presents a modified version of the variable step size (VSS) least mean square (LMS) algorithm originally proposed by Kwong and Johnston [IEEE Trans. Signal Process. 40(7) (July 1992) 1633-1642]. The performance of the new algorithm, called noise resilient variable step size (NRVSS), is less sensitive than VSS to the power of the measurement noise. Its implementation requires only a very small increase in the computational complexity. Analytical models are derived for both NRVSS and VSS algorithms for Gaussian signals and small step-size fluctuations. Simulation results show that the NRVSS algorithm has approximately the same transient behavior as VSS but leads to lower steady-state excess mean-square errors as the signal-to-noise ratio (SNR) decreases. The NRVSS algorithm is specially indicated for adaptive interference reduction in biomedical applications. (C) 2007 Elsevier B.V. All rights reserved.
Keyword:
adaptive filter
LMS
variable step size
VSS
noise suppression
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
IF:
3.6
论文数:
9.9K
被引数:
1.7W
机构
引用论文
Active Power Control to Mitigate Frequency Deviations in Large-Scale Grid-Connected PV System Using Grid-Forming Single-Stage Inverters.png)
Energies
OAAI
EnergiesIF0
OAAI分享收藏
查看更多内容