Complexity reduction of the NLMS algorithm via selective coefficient update

Author

Aboulnasr, T. ; Mayyas, K.

Author_Institution

Sch. of Inf. Technol. & Eng., Ottawa Univ., Ont., Canada

Volume

47

Issue

5

fYear

1999

fDate

5/1/1999 12:00:00 AM

Firstpage

1421

Lastpage

1424

Abstract

This article proposes an algorithm for partial update of the coefficients of the normalized least mean square (NLMS) finite impulse response (FIR) adaptive filter. It is shown that while the proposed algorithm reduces the complexity of the adaptive filter, it maintains the closest performance to the full update NLMS filter for a given number of updates. Analysis of the MSE convergence and steady-state performance for independent and identically distributed (i.i.d.) signals is provided for the extreme case of one update/iteration

Keywords

FIR filters; adaptive filters; adaptive signal processing; computational complexity; filtering theory; least mean squares methods; MSE convergence; NLMS FIR adaptive filter; NLMS algorithm; adaptive echo cancellation; complexity reduction; finite impulse response; i.i.d. signals; independent identically distributed signals; normalized least mean square; one update/iteration; partial coefficient update; selective coefficient update; steady-state performance; Acoustic applications; Adaptive filters; Convergence; Digital signal processing chips; Error correction; Finite impulse response filter; Performance analysis; Signal analysis; Signal processing algorithms; Steady-state;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.757235

Filename

757235