Fast surface-search algorithm for adaptive FIR filtering

Author

Feng, Da-Zheng ; Zheng, Wei-Xing

Author_Institution

Key Lab. for Radar Signal Process., Xidian Univ., Xi´´an, China

Volume

1

fYear

2004

fDate

31 Aug.-4 Sept. 2004

Firstpage

376

Abstract

This paper proposes a fast surface search (FSS) algorithm for adaptive FIR filtering. The proposed algorithm depends on the efficient calculation of the fast gain vector (FGA) defined in C. E. Davila (July 1993) and the rank-one updating formula of the correlation matrix of the input vector sequence. This algorithm is of computational complexity O(M), which is comparable with the fast recursive least squares transversal filters for adaptive FIR filtering. The global convergence of the proposed algorithm is studied by the Lyapunov indirect method. The performances of the relative algorithms are shown via computer simulations.

Keywords

FIR filters; Lyapunov methods; adaptive filters; computational complexity; convergence of numerical methods; correlation methods; matrix algebra; search problems; transversal filters; Lyapunov indirect method; adaptive FIR filtering; computational complexity; correlation matrix; fast gain vector; fast recursive least squares transversal filter; fast surface-search algorithm; input vector sequence; rank-one updating formula; Adaptive filters; Convergence; Filtering algorithms; Finite impulse response filter; Frequency selective surfaces; Least squares methods; Resonance light scattering; Signal processing algorithms; Transversal filters; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on

Print_ISBN

0-7803-8406-7

Type

conf

DOI

10.1109/ICOSP.2004.1452660

Filename

1452660