The Euclidean direction search algorithm for adaptive filtering

Author

Xu, Guo Fang ; Bose, Tamal ; Schroeder, Jim

Author_Institution

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

Volume

3

fYear

1999

fDate

36342

Firstpage

146

Abstract

A new least-squares adaptive algorithm, called the Euclidean Direction Search (EDS) algorithm is investigated for applications in fast adaptive filtering. Based on mathematical analysis and computer simulations, the proposed algorithm is shown to be very efficient for adaptive filtering applications such as noise cancellation and channel equalization. The algorithm features an O(N) computational complexity, fast convergence, improved numerical stability and least-squares optimal solution. Its convergence rate is comparable to that of the RLS but at a much lower computational cost

Keywords

adaptive equalisers; adaptive filters; computational complexity; filtering theory; interference suppression; least squares approximations; numerical stability; Euclidean direction search algorithm; channel equalization; computational complexity; convergence rate; fast adaptive filtering; fast convergence; least-squares adaptive algorithm; least-squares optimal solution; noise cancellation; numerical stability; Adaptive algorithm; Adaptive equalizers; Adaptive filters; Application software; Computational complexity; Computer simulation; Convergence of numerical methods; Filtering algorithms; Mathematical analysis; Noise cancellation;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1999. ISCAS '99. Proceedings of the 1999 IEEE International Symposium on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-5471-0

Type

conf

DOI

10.1109/ISCAS.1999.778806

Filename

778806