Title :
Subband adaptive convex combination of two NLMS based filters for sparse impulse response systems
Author :
Sohn, Sang-Wook ; Lee, Jeongkyu ; Lee, Kyeong-Pyo ; Choi, Hun ; Bae, Hyeon-Deok
Abstract :
It is well known, combination scheme is suitable for improving the performance of adaptive algorithms. In this paper, we propose a subband combination scheme for sparse impulse response systems. The combination is carried out in subband domain. In this convex combination, SIPNLMS and SNLMS are derived for fast convergence and small steady state error respectively. And mixing parameters are described by minimum mean square error and stochastic gradient algorithm. In adaptive system identification scenario, the advantages of this proposed method are illustrated.
Keywords :
adaptive filters; convergence; least mean squares methods; stochastic processes; transient response; NLMS based filters; SIPNLMS; SNLMS; adaptive algorithms; adaptive system identification scenario; fast convergence; mixing parameters; small steady state error; sparse impulse response system; stochastic gradient algorithm; subband adaptive convex combination scheme; Adaptation models; Adaptive filters; Adaptive systems; Convergence; Filtering algorithms; Signal processing algorithms; Steady-state; NLMS; adaptive filter; convex; sparse system; subband;
Conference_Titel :
Statistical Signal Processing Workshop (SSP), 2012 IEEE
Conference_Location :
Ann Arbor, MI
Print_ISBN :
978-1-4673-0182-4
Electronic_ISBN :
pending
DOI :
10.1109/SSP.2012.6319660