Title :
An improverd variable step size LMS adaptive filtering algorithm
Author :
Pingping, Li ; TengDa, Pei ; BingNan, Pei ; LiJun, Hu
Author_Institution :
Sch. of Inf. Eng., Dalian Univ., Dalian, China
Abstract :
LMS (least mean square) algorithm is widely used due to its simple and stable performance. As is well known, there is an inherent conflict between the convergence rate and steady-state misadjustment, which can be overcome through the adjustment of size factor. The paper has analyzed some LMS algorithms that already existed and a new improved variable step-size LMS algorithm is presented. The computer simulation results are consistent with the theoretic analysis, Which show that the algorithm not only has a faster convergence rate, but also has a smaller steady-state error.
Keywords :
adaptive filters; least mean squares methods; convergence rate; improved variable step size LMS adaptive filtering algorithm; least mean square algorithm; stead-state misadjustment; Adaptive filters; Algorithm design and analysis; Computer simulation; Convergence; Educational institutions; Equations; Error correction; Filtering algorithms; Least squares approximation; Steady-state; LMS algorithm; convergence rate; steady-state error; variable step-size;
Conference_Titel :
Information, Computing and Telecommunication, 2009. YC-ICT '09. IEEE Youth Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-5074-9
Electronic_ISBN :
978-1-4244-5076-3
DOI :
10.1109/YCICT.2009.5382451