A variable step-size filtered-x least mean square algorithm for continuously varying noise

2016 ◽  
Vol 64 (4) ◽  
pp. 469-484 ◽  
Author(s):  
Amrita Puri ◽  
Subodh V. Modak ◽  
Kshitij Gupta
2021 ◽  
pp. 107754632110228
Author(s):  
Yubin Fang ◽  
Xiaojin Zhu ◽  
Xiaobing Zhang

The variable step size least mean square algorithm has been suggested since a number of years as a potential solution for improving the performance of least mean square algorithm. In this article, the variable step size least mean square algorithm is classified by the techniques which are used to update step size. Unfortunately, for variable step size least mean square algorithms with forgetting factor, a constant forgetting factor may slow down its convergence speed. For this reason, a variable forgetting factor method for variable step size least mean square is proposed in this article. First, the convergence analysis of a new variable step size least mean square algorithm with the variable forgetting factor is provided. Then, simulations expose the characteristics of this variable forgetting factor method. Last, a micro-vibration control experimental system is established. Four typical variable step size least mean square algorithms and their variable forgetting factor modified version are verified through experiments. The results show that the proposed variable forgetting factor method can effectively improve convergence speed while maintaining the steady-state performance of the variable step size least mean square algorithm with the constant forgetting factor.


2017 ◽  
Vol 5 (2) ◽  
Author(s):  
Monisha Bairagya

In mobile communication using smart antenna, the capacity of a cellular network can be enhanced significantly. Adaptive beamforming is one of the critical issues in smart antenna. A comparative study of beamforming algorithms by using their variable step size parameter like, variable step size least mean square algorithm (VSLMS) and variable step size normalized least mean square algorithm (VSNLMS) are presented in this paper. Smart antennas of 8 elements and 10 elements linear array are considered here. It is found that using VSNLMS algorithm a lower side lobe level is achieved compared to VSLMS algorithm for various angles of desired user and undesired interferer.


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