Combination-Based Affine Projection Generalized Maximum Correntropy Algorithms for Robust Adaptive FilteringCombination-Based Affine Projection Generalized Maximum...J. Zhao et al.

被引：0

作者：

Ji Zhao ^{[1
]}

Xiaoyi Zhu ^{[1
]}

Qiang Li ^{[1
]}

Hongbin Zhang ^{[2
]}

机构：

[1] Southwest University of Science and Technology,School of Information and Control Engineering

[2] University of Electronic Science and Technology of China,School of Information and Communication Engineering

来源：

Signal, Image and Video Processing | 2025年 / 19卷 / 9期

关键词：

Adaptive Filtering; Affine Projection; Convex Combination; Generalized Correntropy; System Identification;

D O I：

10.1007/s11760-025-04331-0

中图分类号：

学科分类号：

摘要：

In environments heavily influenced by outliers, the affine projection generalized maximum correntropy (APGMC) algorithm outperforms existing AP-like algorithms in robustness and effectiveness. Generally, APGMC achieves fast convergence with large step sizes while maintaining high filtering accuracy with smaller ones. To reconcile these strengths, we utilize a combined strategy incorporating two distinct approaches for the mixing parameter, i.e., the classical exponential method and the S-type function renowned for its computational efficiency. Simulation results validate the superiority of our proposed algorithms in system identification, particularly in environments challenged by heavily non-Gaussian impulsive noise.

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