A Hybrid Approach for Sparse Adaptive Filters Under Highly Colored Inputs
We address an adaptive filtering problem for sparse linear systems excited by highly colored input signals. A proportionate approach is known to accelerate the convergence speed by exploiting the sparseness of the systems, while a transformdomain approach is known to alleviate the decay of the convergence rate for highly colored inputs. We highlight the improved proportionate NLMS (IPNLMS) and transform-domain NLMS (TD-NLMS) algorithms. The present experimental results show that the gain of IPNLMS against TD-NLMS changes from positive to negative as the input auto-correlation becomes strong. We propose a hybrid approach of IPNLMS and TD-NLMS, taking the advantages of both algorithms by means of a timevariant convex combination of the two matrices employed by those algorithms. Numerical examples show the efficacy of the proposed algorithm.
Osamu Toda Masahiro Yukawa Shigenobu Sasaki Hisakazu Kikuchi
Department of Electrical and Electronic Engineering, Niigata University, Japan
国际会议
2011亚太信号与信息处理协会年度峰会(APSIPAASC 2011)
西安
英文
1-5
2011-10-18（万方平台首次上网日期，不代表论文的发表时间）