A variable forgetting factor RLS adaptive filtering algorithm

Author

Wang, Junfeng

Author_Institution

Coll. of Comput. Sci. & Technol., Henan Polytech. Univ., Jiaozuo, China

fYear

2009

fDate

27-29 Oct. 2009

Firstpage

1127

Lastpage

1130

Abstract

The recursive least squares algorithm (RLS) is realized in MATLAB. Simulation results show that forgetting factor influences the algorithm convergence and stability, which will significantly affect the performance of adaptive filter. Therefore, a variable forgetting factor RLS algorithm is presented in this paper. Simulation results show that the convergence and stability of the variable forgetting factor RLS algorithm (VRLS) are superior to ordinary RLS algorithm. Finally, the RLS algorithm is applied in channel equalization in low SNR and high SNR.

Keywords

adaptive filters; equalisers; least squares approximations; mathematics computing; MATLAB; adaptive filtering; channel equalization; high SNR; low SNR; recursive least squares algorithm; variable forgetting factor; Adaptive algorithm; Adaptive filters; Convergence; Educational institutions; Filtering algorithms; Finite impulse response filter; Least squares approximation; Least squares methods; Resonance light scattering; Stability; Adaptive filter; Channel equalization; RLS; Variable forgetting factor;

fLanguage

English

Publisher

ieee

Conference_Titel

Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, 2009 3rd IEEE International Symposium on

Conference_Location

Beijing

Print_ISBN

978-1-4244-4076-4

Type

conf

DOI

10.1109/MAPE.2009.5355946

Filename

5355946