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Robust Time-Varying Parameter Proportionate Affine-Projection-Like Algorithm for Sparse System Identification.
- Source :
-
Circuits, Systems & Signal Processing . Jul2021, Vol. 40 Issue 7, p3395-3416. 22p. - Publication Year :
- 2021
-
Abstract
- Due to its low computational burden, the affine-projection-like (APL) adaptive filtering algorithm has been extensively studied for colored signal input. Recently, a robust APL algorithm was designed by adopting the M-estimate cost function in impulsive noise environment; however, its convergence rate is very slow for sparse system identification. This paper proposed a proportionate APL M-estimate (PAPLM) algorithm, which is derived by using the proportionate matrix to heighten the convergence rate. To maintain good steady-state performance of the PAPLM algorithm, a time-varying parameter PAPLM (TV-PAPLM) algorithm is proposed, which uses a modified exponential function to adjust the time-varying parameter according to the ratio of the mean square score function to the system noise variance. Moreover, the steady-state excess mean-square error performance of PAPLM algorithm is analyzed and obtained in detail. Simulation results reveal that the proposed PAPLM and TV-PAPLM algorithms achieve fast convergence rate and good steady-state performance in sparse system identification. [ABSTRACT FROM AUTHOR]
- Subjects :
- *ALGORITHMS
*ADAPTIVE filters
*EXPONENTIAL functions
*COST functions
Subjects
Details
- Language :
- English
- ISSN :
- 0278081X
- Volume :
- 40
- Issue :
- 7
- Database :
- Academic Search Index
- Journal :
- Circuits, Systems & Signal Processing
- Publication Type :
- Academic Journal
- Accession number :
- 150933785
- Full Text :
- https://doi.org/10.1007/s00034-020-01628-y