稳健性(进化)
算法
趋同(经济学)
计算机科学
投影(关系代数)
收敛速度
仿射变换
自适应滤波器
计算复杂性理论
数学优化
数学
电信
生物化学
经济增长
基因
频道(广播)
经济
化学
纯数学
作者
Ji Zhao,Xia Ni,Qiang Li,Lingli Tang,Hongbin Zhang
标识
DOI:10.1109/lsp.2024.3402343
摘要
The affine projection sign algorithm (APSA) has garnered significant attention in adaptive filtering due to its exceptional robustness and reduced computational demands. Nevertheless, the inherent use of a fixed projection order in APSA can compromise filtering accuracy and convergence speed. To address this issue, we introduce an innovative strategy for dynamically updating the projection order, resulting in an enhanced version of APSA called the evolving order based APSA (E-APSA). This evolving strategy compares the instantaneous power of output error to a threshold determined by the steady-state mean-square error of APSA, thereby enabling variable projection orders. Furthermore, we provide computational complexity and convergence analyses for E-APSA. Simulation results demonstrate that, compared to other related algorithms, E-APSA offers a significantly faster convergence rate while maintaining competitive steady-state misalignment.
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