Adaptive recursive least squares algorithm for joint FIR filtering and post-delay tracking in the process identification

Author

Xingxing, Yu ; Dali, Zhang ; PingFan, Yan

Author_Institution

Dept. of Autom., Tsinghua Univ., Beijing, China

Volume

1

fYear

1997

fDate

28-31 Oct 1997

Firstpage

783

Abstract

The joint FIR filtering and post delay tracking system identification problem is considered. The input signal to the unknown system is first filtered then delayed. An adaptive recursive least squares algorithm based on fast transversal filters is developed, which improves the algorithm proposed by D. Boudreau and P. Kabal (1993) by reducing the time complexity from O(19p) to O(7p). Its convergence and delay tracking properties are demonstrated by the identification of an LPS and linearly changing delay series system

Keywords

FIR filters; adaptive systems; computational complexity; least squares approximations; signal processing; tracking; LPS; adaptive recursive least squares algorithm; delay tracking properties; fast transversal filters; input signal; joint FIR filtering; linearly changing delay series system; post delay tracking; process identification; system identification problem; time complexity; unknown system; Adaptive filters; Delay effects; Delay estimation; Delay lines; Filtering algorithms; Finite impulse response filter; Least squares approximation; Least squares methods; Nonlinear filters; Transversal filters;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-4253-4

Type

conf

DOI

10.1109/ICIPS.1997.672896

Filename

672896