Affine Projection Algorithm With Outlier Detection for Robust Filtering

被引：0

作者：

Hou, Yunxian ^{[1
,2
]}

Li, Guoliang ^{[1
,2
]}

Zhang, Huaiyuan ^{[1
,2
]}

Zhang, Hongbin ^{[1
,2
]}

Zhao, Ji ^{[1
,2
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 610054, Peoples R China

[2] Southwest Univ Sci & Technol, Sch Informat Engn, Mianyang 621010, Peoples R China

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS | 2024年 / 71卷 / 11期

基金：

中国国家自然科学基金;

关键词：

Noise; Switches; Mathematical models; Computational complexity; Anomaly detection; Convergence; Steady-state; Adaptive filter; affine projection; outlier detection; impulsive noise; system identification; FAMILY;

D O I：

10.1109/TCSII.2024.3404494

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this brief, a new adaptive filtering algorithm called affine projection robust outlier detection algorithm (APRODA) that combines affine projection (AP) method and outlier detection is proposed. The convergence speed of traditional AP-type algorithms is easily affected by impulsive noise. APRODA enhances impulsive noise resistance by removing the outliers generated by impulsive noise. Also, a new step-size adjustment method is proposed. This method greatly reduces the computational complexity of the traditional step-size adjustment method by switching the step-size through the detection of steady state and mutation. Combined with APRODA, switched-APRODA is proposed. Several simulation experiments show that the proposed algorithms are significantly preferable to other AP-type algorithms in terms of convergence speed and tracking ability for system identification.

引用

页码：4778 / 4782

页数：5