New FIR adaptive filtering algorithm based on quantized gradients and least-squares convergence factors

Author

Demeechai, T.

Author_Institution

Dept. of Telecommun., Mahanakom Univ. of Technol., Bankok, Thailand

Volume

46

Issue

2

fYear

1999

fDate

2/1/1999 12:00:00 AM

Firstpage

210

Lastpage

211

Abstract

A new FIR adaptive filtering algorithm, using quantized gradients with a variable convergence factor that minimizes an exponentially weighted sum square error, is proposed. The proposed algorithm converges about as fast as the optimum block adaptive shifting algorithm does. However, when effective reusing data length due to the exponential weighting is a power-of-two number, the proposed algorithm requires a much smaller number of multiplications and divisions

Keywords

FIR filters; adaptive filters; convergence of numerical methods; errors; filtering theory; least squares approximations; FIR adaptive filtering algorithm; divisions; error minimization; exponentially weighted sum square error; least-squares convergence factors; multiplications; quantized gradients; variable convergence factor; Adaptive filters; Computer errors; Computer simulation; Convergence; Filtering algorithms; Finite impulse response filter; Least squares approximation; Quantization; Signal processing algorithms; Telecommunication computing;

fLanguage

English

Journal_Title

Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7130

Type

jour

DOI

10.1109/82.752955

Filename

752955