Multiplier-free NLMS for adaptive IIR filtering

Author

Ameer, Salah ; Shahravva, Behnam

Author_Institution

Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont.

fYear

2005

fDate

1-4 May 2005

Firstpage

1237

Lastpage

1240

Abstract

Using geometric series expansion, a multiplier-free version of the NLMS is proposed for adaptive IIR filtering. Inputs rather than the coefficients are quantized to the next power of 2. Hence, single quantization is done per data sample. A different approach in deriving the NLMS is also presented. Simulation results in system identification illustrate the usefulness of the proposed algorithm, even for long durations (poles near the unit circle) and non-exact modeling

Keywords

IIR filters; adaptive filters; filtering theory; least mean squares methods; adaptive IIR filtering; multiplier-free NLMS; single quantization; system identification; Adaptive filters; Convergence; Filtering; Finite impulse response filter; IIR filters; Least squares approximation; Quantization; Signal processing algorithms; Stability; System identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 2005. Canadian Conference on

Conference_Location

Saskatoon, Sask.

ISSN

0840-7789

Print_ISBN

0-7803-8885-2

Type

conf

DOI

10.1109/CCECE.2005.1557201

Filename

1557201

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2761531