Title :
Proportionate improved normalized subband adaptive filter algorithm for highly noisy sparse system
Author :
Yi Yu;Haiquan Zhao
Author_Institution :
School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China
Abstract :
In order to speed up the convergence of the recently-presented improved normalized subband adaptive filter (INSAF) algorithm in sparse systems, this paper derives its proportionate update based on the concept of the Riemannian distance between the tap-weight vectors. Also, together with the previous improved method of calculating the proportionate matrix, an improved proportionate INSAF (IP-INSAF) algorithm is obtained. Simulation results, in the context of acoustic echo cancellation with a low signal-noise-ratio (SNR), demonstrate the superiority of the proposed algorithm for sparse systems.
Keywords :
"Signal processing algorithms","Convergence","Signal to noise ratio","Adaptive filters","Algorithm design and analysis","Speech","Filter banks"
Conference_Titel :
Signal Processing, Communications and Computing (ICSPCC), 2015 IEEE International Conference on
Print_ISBN :
978-1-4799-8918-8
DOI :
10.1109/ICSPCC.2015.7338781