An Enhanced Affine Projection Algorithm Based on the Adjustment of Input-Vector Numberopen access
- Authors
- Shin, Jaewook; Kim, Jeesu; Kim, Tae-Kyoung; Yoo, Jinwoo
- Issue Date
- Mar-2022
- Publisher
- MDPI
- Keywords
- adaptive filter; affine projection algorithm; input-vector number; adjustment; convergence rate; steady-state estimation error; filter performance
- Citation
- ENTROPY, v.24, no.3
- Journal Title
- ENTROPY
- Volume
- 24
- Number
- 3
- URI
- https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/21023
- DOI
- 10.3390/e24030431
- ISSN
- 1099-4300
1099-4300
- Abstract
- An enhanced affine projection algorithm (APA) is proposed to improve the filter performance in aspects of convergence rate and steady-state estimation error, since the adjustment of the input-vector number can be an effective way to increase the convergence rate and to decrease the steady-state estimation error at the same time. In this proposed algorithm, the input-vector number of APA is adjusted reasonably at every iteration by comparing the averages of the accumulated squared errors. Although the conventional APA has the constraint that the input-vector number should be integer, the proposed APA relaxes that integer-constraint through a pseudo-fractional method. Since the input-vector number can be updated at every iteration more precisely based on the pseudo-fractional method, the filter performance of the proposed APA can be improved. According to our simulation results, it is demonstrated that the proposed APA has a smaller steady-state estimation error compared to the existing APA-type filters in various scenarios.
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