Behavior of the LMS algorithm with hyperbolic secant cost

This paper presents a new least mean square (LMS) algorithm with defining hyperbolic secant cost function. Then, the detailed analysis is conducted to reveal the behavior of the proposed algorithm. The transient analysis is conducted based on a Taylor expansion approach and energy conservation (EC)...

Full description

Saved in:
Bibliographic Details
Published inJournal of the Franklin Institute Vol. 357; no. 3; pp. 1943 - 1960
Main Authors Lu, Lu, Chen, Lihui, Zheng, Zongsheng, Yu, Yi, Yang, Xiaomin
Format Journal Article
LanguageEnglish
Published Elmsford Elsevier Ltd 01.02.2020
Elsevier Science Ltd
Subjects
Algorithms
Computer simulation
Cost analysis
Cost function
Energy conservation
Error analysis
Hyperbolic functions
Mean square errors
Noise
Performance enhancement
Random noise
Stability analysis
Taylor series
Transient analysis
Online AccessGet full text
ISSN0016-0032
1879-2693
0016-0032
DOI10.1016/j.jfranklin.2019.12.040

Cover

More Information
Summary:This paper presents a new least mean square (LMS) algorithm with defining hyperbolic secant cost function. Then, the detailed analysis is conducted to reveal the behavior of the proposed algorithm. The transient analysis is conducted based on a Taylor expansion approach and energy conservation (EC) relation expression. Following the results of transient state analysis of excess means square-error (EMSE), we achieve the steady-state EMSE and mean-square deviation (MSD) expressions of the proposed algorithm. Moreover, the sufficient condition for the stability convergence is given. Simulation results validate the theoretical analyses and demonstrate the enhanced performance of the proposed algorithm as compared with conventional LMS algorithm in the presence of white Gaussian noise (WGN) and uniform noise.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0016-0032
1879-2693
0016-0032
DOI:10.1016/j.jfranklin.2019.12.040