Title :
A Convex Combination LMS Algorithm Based on Krylov Subspace Transform
Author :
Li, Ning ; Zhang, Yonggang ; Wang, Chengcheng
Author_Institution :
Coll. of Autom., Harbin Eng. Univ., Harbin, China
Abstract :
A convex combination LMS (least mean square) algorithm based on Krylov subspace transform is proposed in this paper. In this approach, impulse response of the unknown system is firstly transformed into Krylov subspace, in which the system structure is changed into sparse. Then an improved proportionate normalized LMS (IPNLMS) algorithm and a variable tap-length normalized LMS (VTNLMS) algorithm are combined. Simulations are performed to show the convergence performance of the combined algorithm. The results show that both a fast convergence rate and small steady state mean square deviation (MSD) are obtained.
Keywords :
adaptive filters; convergence of numerical methods; least mean squares methods; linear algebra; transforms; transient response; IPNLMS algorithm; Krylov subspace transform; MSD; VTNLMS algorithm; adaptive filters; convergence performance; convex combination LMS algorithm; fast convergence rate; improved proportionate normalized LMS algorithm; impulse response; least mean squares algorithm; steady state mean square deviation; variable tap-length normalized LMS algorithm; Algorithm design and analysis; Convergence; Least squares approximation; Signal processing algorithms; Steady-state; Transforms; Vectors; Adaptive filters; Krylov subspace; convex combination;
Conference_Titel :
Computational Sciences and Optimization (CSO), 2012 Fifth International Joint Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4673-1365-0
DOI :
10.1109/CSO.2012.180
