A Modified FBLMS Algorithm Research and Performance Analysis

Author

Qi Hua ; Guo Tian-Yi ; Lian Bao-wan ; Liu Jun

Author_Institution

Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´an, China

fYear

2009

fDate

26-28 Dec. 2009

Firstpage

3717

Lastpage

3721

Abstract

As there is a conflict about block step size between the requirements of the convergence velocity and parameters´ maladjustment within FBLMS algorithm, a modified FBLMS algorithm is well presented in this paper which uses a variable block step size to solve the contradiction between convergence rate and precision. The modified FBLMS algorithm is simulated in the MATLAB platform. The simulation results prove that this algorithm not only has a faster convergence speed, a faster tracking speed and a smaller stationary error, but also has a better anti-jamming capability.

Keywords

computational complexity; convergence; convolution; least mean squares methods; mathematics computing; Matlab simulation; antijamming capability; convergence velocity; modified FBLMS algorithm; parameters maladjustment; stationary error; tracking speed; variable block step size; Adaptive algorithm; Adaptive filters; Convergence; Educational institutions; Eigenvalues and eigenfunctions; Equations; Information science; Least squares approximation; Performance analysis; Time domain analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Science and Engineering (ICISE), 2009 1st International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4244-4909-5

Type

conf

DOI

10.1109/ICISE.2009.71

Filename

5454497