Volume 9, Issue 1 (March 2013)                   IJEEE 2013, 9(1): 27-35 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Shams Esfand Abadi M, Shafiee M. A Family of Variable Step-Size Normalized Subband Adaptive Filter Algorithms Using Statistics of System Impulse Response. IJEEE 2013; 9 (1) :27-35
URL: http://ijeee.iust.ac.ir/article-1-550-en.html
A Family of Variable Step-Size Normalized Subband Adaptive Filter Algorithms Using Statistics of System Impulse Response
M. Shams Esfand Abadi , M.S. Shafiee
Abstract:   (6758 Views)
This paper presents a new variable step-size normalized subband adaptive filter (VSS-NSAF) algorithm. The proposed algorithm uses the prior knowledge of the system impulse response statistics and the optimal step-size vector is obtained by minimizing the mean-square deviation(MSD). In comparison with NSAF, the VSS-NSAF algorithm has faster convergence speed and lower MSD. To reduce the computational complexity of VSSNSAF, the VSS selective partial update NSAF (VSS-SPU-NSAF) is proposed where the filter coefficients are partially updated in each subband at every iteration. We demonstrated the good performance of the proposed algorithms in convergence speed and steady-state MSD for a system identification set-up.
Keywords: Adaptive filter , Normalized Subband Adaptive Filter (NSAF) , Selective Partial Update , SPU , Variable Step-Size , VSS
Full-Text [PDF 414 kb]   (3004 Downloads)    
Type of Study: Research Paper | Subject: Signal Processing
Received: 2013/01/28 | Revised: 2013/03/18 | Accepted: 2013/03/18
Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Creative Commons License
© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.