A new efficient LMS adaptive filtering algorithm

Author

Chen, Sau-Gee ; Kao, Yung-An ; Tsai, Kwung-Yee

Author_Institution

Dept. of Electron. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan

fYear

1994

fDate

22-26 Aug 1994

Firstpage

644

Abstract

A new LMS adaptive filtering algorithm is proposed. The algorithm has comparable performance to the direct-form LMS algorithm (DLMS), while costs N/2-1 less multiplications at the expense of N/2+3 more additions than DLMS algorithm. For coefficient update, the new algorithm needs one additional coefficient estimation. Further, the algorithm is combined with LMS sign algorithm (SA), signed regressor algorithm (SRA) and zero forcing (ZFA) algorithm for further complexity reduction. Simulation results confirm with theoretical analysis that the new algorithm and its SA, SRA and ZFA versions converge as fast as their counter DLMS algorithms, while maintaining comparable performance

Keywords

adaptive filters; convolution; least mean squares methods; LMS sign algorithm; coefficient estimation; coefficient update; complexity reduction; direct-form LMS algorithm; efficient LMS adaptive filtering algorithm; signed regressor algorithm; zero forcing algorithm; Adaptive algorithm; Adaptive filters; Algorithm design and analysis; Analytical models; Convolution; Costs; Counting circuits; Filtering algorithms; Least squares approximation; Performance analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON '94. IEEE Region 10's Ninth Annual International Conference. Theme: Frontiers of Computer Technology. Proceedings of 1994

Print_ISBN

0-7803-1862-5

Type

conf

DOI

10.1109/TENCON.1994.369225

Filename

369225