Improved variable step-size LMS algorithm based on hyperbolic tangent function

Jianwu ZHANG; Hao YU; Qianhua ZHANG

doi:10.11959/j.issn.1000-436x.2020224

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Improved variable step-size LMS algorithm based on hyperbolic tangent function

Papers | 更新时间：2024-06-05

- Improved variable step-size LMS algorithm based on hyperbolic tangent function
- Journal on Communications Vol. 41, Issue 11, Pages: 116-123(2020)
- 作者机构：
  
  1. 杭州电子科技大学通信工程学院，浙江杭州 310018
  2. 之江实验室智能网络研究中心，浙江杭州 311121
- 作者简介：
- 基金信息：
  
  The Project of Industrial Technology Basic Public Service Platform of the Ministry of Industry and Information Technology in 2019(2019-00891-2-1)
- DOI：10.11959/j.issn.1000-436x.2020224
  CLC： TN927
- Online First：2020-11，
  
  Published：25 November 2020
- 稿件说明：
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Jianwu ZHANG, Hao YU, Qianhua ZHANG. Improved variable step-size LMS algorithm based on hyperbolic tangent function[J]. Journal on Communications, 2020, 41(11): 116-123.
DOI：

Jianwu ZHANG, Hao YU, Qianhua ZHANG. Improved variable step-size LMS algorithm based on hyperbolic tangent function[J]. Journal on Communications, 2020, 41(11): 116-123. DOI： 10.11959/j.issn.1000-436x.2020224.

摘要

为了解决定步长 LMS 算法不能同时满足快速收敛和低稳态误差的问题，提出了一种基于改进双曲正切函数的变步长LMS算法（IVSSLMS）。该算法利用步长反馈因子的二范数和误差信号的相关值来调节步长，克服了定步长算法收敛速度慢及抗噪声能力差的问题；并从理论上分析了算法的性能，给出了参数的取值方法。仿真实验结果表明，在高/低信噪比条件下，IVSSLMS 算法比已有变步长算法的收敛速度更快、稳态误差更小、系统跟踪能力更优。

Abstract

In order to improve that the LMS algorithm for determining step size cannot satisfy both rapid convergence and low steady-state misalignment errors

a variable step size algorithm (IVSSLMS) based on an improved hyperbolic tangent function was proposed.The step size feedback factor and the correlation value of the error signal were used to adjust the step size

and the problems of slow convergence speed and poor anti-noise ability of the fixed-step size algorithm was overcame.The performance and parameters settings of the proposed algorithm were analyzed.The simulation results show that IVSSLMS has a faster convergence rate

lower steady-state error and better system tracking capability than the existing variable step size algorithms under high and low SNR conditions.

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references

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