A new variable step size method for the LMS adaptive filter

Author

Sanubari, Junibakti

Author_Institution

Dept. of Electron. Eng., Satya Wacana Univ., Salatiga

Volume

1

fYear

2004

fDate

6-9 Dec. 2004

Firstpage

501

Abstract

In this paper, a new cost function for improving the performance of the least mean square (LMS) method is proposed. The proposed cost function is convex. The first derivative of the proposed cost function is continued. The proof of the convexity of the function is presented. The theoretical study of the convergence characteristic shows that lower error and faster convergence can be obtained by using the proposed function. The proposed function provide large weighting factor when the error is small. On the hand, when the error is large, a small weighting factor is applied. By doing so, the effect of the noise can be reduced. The simulation results show that indeed we can lower final error and faster convergence when small alpha is applied

Keywords

adaptive filters; convergence; least mean squares methods; LMS adaptive filter; LMS method; convergence characteristic; cost function; function convexity; least mean square; noise effect; variable step size method; weighting factor; Adaptive algorithm; Adaptive filters; Convergence; Cost function; Least squares approximation; Least squares methods; Mean square error methods; Noise reduction; Transfer functions; Variable structure systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2004. Proceedings. The 2004 IEEE Asia-Pacific Conference on

Conference_Location

Tainan

Print_ISBN

0-7803-8660-4

Type

conf

DOI

10.1109/APCCAS.2004.1412808

Filename

1412808