Analysis of the Euclidean direction set adaptive algorithm

Author

Xu, Guo-Fang ; Bose, Tamal

Author_Institution

Dept. of Electr. Eng., Colorado Univ., Denver, CO, USA

Volume

3

fYear

1998

fDate

12-15 May 1998

Firstpage

1689

Abstract

A mathematical analysis is performed on a previously reported gradient-based adaptive algorithm named the Euclidean direction set (EDS) method. It has been shown that the EDS algorithm has a computational complexity of O(N) for each system update, and a rate of convergence (based on computer simulations) comparable to the RLS algorithm. The stability of the EDS method is studied and it is shown that the algorithm converges to the true solution. It is also proved that the convergence rate of the EDS method is superior to that of the steepest descent method

Keywords

adaptive filters; adaptive signal processing; computational complexity; filtering theory; matrix algebra; numerical stability; optimisation; search problems; set theory; Euclidean direction set; RLS algorithm; adaptive filtering; computational complexity; computer simulations; convergence rate; gradient-based adaptive algorithm; matrix; stability; steepest descent method; Adaptive algorithm; Adaptive filters; Algorithm design and analysis; Computational complexity; Computer simulation; Convergence; Filtering algorithms; Mathematical analysis; Newton method; Resonance light scattering;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on

Conference_Location

Seattle, WA

ISSN

1520-6149

Print_ISBN

0-7803-4428-6

Type

conf

DOI

10.1109/ICASSP.1998.681781

Filename

681781