Back to Search
Start Over
A Switching-Based Variable Step-Size PNLMS Adaptive Filter for Sparse System Identification.
- Source :
-
Circuits, Systems & Signal Processing . Jan2024, Vol. 43 Issue 1, p568-592. 25p. - Publication Year :
- 2024
-
Abstract
- The standard proportionate normalized least mean square (PNLMS) adaptive algorithm suffers from convergence performance limitation due to a constant step-size during the convergence period. In this paper, a switching-based variable step-size PNLMS is proposed to improve the convergence performance in sparse system identification. To adjust the step-size, the convergence performance of PNLMS is first analysed in the statistical sense and by exploiting the analysis, a switching-based method is then proposed, which brings about a fast convergence towards the desired steady-state mean-square weight deviation. The step-size reduces during the convergence period in a few steps, while in the case of abrupt change in the system impulse response, the step-size increases to its initial value. A sub-band version of the proposed adaptive algorithm is further proposed for highly correlated input signals. Simulation results confirm the superiority of the proposed full-band and sub-band algorithms in terms of convergence performance compared to some competing adaptive algorithms. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0278081X
- Volume :
- 43
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Circuits, Systems & Signal Processing
- Publication Type :
- Academic Journal
- Accession number :
- 174759445
- Full Text :
- https://doi.org/10.1007/s00034-023-02490-4