A General Least Mean Square Algorithm Based on Mean Square Deviation Analysis

Xiaoping XIE; Xiongkun SHI

doi:10.11999/JEIT200639

Volume 43 Issue 8

Aug. 2021

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Xiaoping XIE, Xiongkun SHI. A General Least Mean Square Algorithm Based on Mean Square Deviation Analysis[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2249-2257. doi: 10.11999/JEIT200639

Citation:

Xiaoping XIE, Xiongkun SHI. A General Least Mean Square Algorithm Based on Mean Square Deviation Analysis[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2249-2257. doi: 10.11999/JEIT200639

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A General Least Mean Square Algorithm Based on Mean Square Deviation Analysis

doi: 10.11999/JEIT200639

Xiaoping XIE,
Xiongkun SHI^,

State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410012, China

Received Date: 2020-07-30
Rev Recd Date: 2020-12-07

Available Online: 2020-12-17

Publish Date: 2021-08-10

Abstract

Abstract

Whether it is the traditional fixed step size or the newly proposed Least Mean Square (LMS) algorithm, a priori estimation of the algorithm parameters is required to achieve better results when processing signals of specific mathematical features. However, in the actual signal processing process, the estimation of the algorithm parameters is a very difficult process. In this paper, the mean square deviation and convergence characteristics of LMS algorithm are analyzed, and a variable step size LMS algorithm with relative error as variable is proposed, which can realize self-estimation of step control parameters. It can adapt signals of different mathematical features. The example shows that the new algorithm has faster convergence speed and smaller mean square error.
- Mean square deviation analysis,
- Adaptive filter,
- Relative error,
- Universality

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References(17)

References

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