A Unified Affine-Projection-Like Adaptive Algorithm for System Identification
Yingsong Li, Yonglin Fu, Yongchun Miao, Zhixiang Huang, Paulo S. R. Diniz
Abstract
A unified affine-projection-like adaptive (UAPLA) algorithm is devised and verified for system identification. The UAPLA algorithm uses a generalized cost function encompassing some data-reusing methods to cope with colored input signals. Furthermore, the UAPLA algorithm is derived based on the new cost function to approximate several affine-projection algorithms. As a result, the proposed UAPLA algorithm approximates some classical adaptive filters that can be considered as special cases of the UAPLA, allowing flexibility to achieve low estimation errors under impulsive noises. The obtained results conducted by simulations help to corroborate the superiority of the proposed UAPLA algorithm over other popular AP algorithms.