Adaptive system identification using fuzzy inference based LMS algorithm

Author

Ryu, Geun-Taek ; Kim, Dong-Won ; Choe, Jung-Go ; Kim, Dae-sung ; Bae, Hyeon-Deok

Author_Institution

Dept. of Electron. Telecommun., Chungbuk Coll., South Korea

Volume

1

fYear

1996

fDate

14-18 Oct 1996

Firstpage

587

Abstract

A fuzzy LMS algorithm is presented. The algorithm uses fuzzy inference to obtain the adaptive gain at every iteration of the LMS algorithm. The adaptive gain is obtained by a fuzzy system which has two inputs, an error signal and a one-step previous adaptive gain. This algorithm is applied to adaptive system identification of a hybrid system in a telecommunication network. In the experimental results, the proposed fuzzy LMS adaptive algorithm shows a better performance than than the LMS algorithm in terms of the convergence speed

Keywords

adaptive filters; adaptive signal processing; convergence of numerical methods; filtering theory; fuzzy systems; identification; inference mechanisms; least mean squares methods; telecommunication networks; LMS algorithm; adaptive filter; adaptive gain; adaptive system identification; convergence speed; experimental results; fuzzy inference; fuzzy system; hybrid system; performance; telecommunication network; Adaptive algorithm; Adaptive filters; Adaptive systems; Convergence; Fuzzy sets; Fuzzy systems; Inference algorithms; Least squares approximation; System identification; Telecommunications;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 1996., 3rd International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-2912-0

Type

conf

DOI

10.1109/ICSIGP.1996.567332

Filename

567332