Diffusion Partitioned-Block Frequency-Domain Adaptive Filter Over Multitask Networks

被引：1

作者：

Han, Hongyu ^{[1
]}

Peng, Yishu ^{[2
]}

Zhang, Fenglian ^{[2
]}

Le, Dinh Cong ^{[3
]}

Zhang, Sheng ^{[2
]}

机构：

[1] Sichuan Normal Univ, Sch Comp Sci, Chengdu 610068, Peoples R China

[2] Southwest Jiaotong Univ, Sch Informat Sci & Technol, Chengdu 611756, Peoples R China

[3] Vinh Univ, Sch Engn & Technol, Vinh, Nghe An, Vietnam

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS | 2023年 / 70卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Frequency-domain analysis; Clustering algorithms; Partitioning algorithms; Adaptive systems; Indexes; Delays; Transforms; Adaptive networks; frequency-domain; diffusion strategy; adaptive combination weight; LMS; ADAPTATION; IMPLEMENTATION; STRATEGIES;

D O I：

10.1109/TCSII.2022.3225364

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：

As a generalization of the frequency-domain adaptive filter (FDAF) algorithm, partitioned-block frequency-domain adaptive filter (PBFDAF) results in minimal signal path delay. In this brief, we propose the diffusion normalized PBFDAF algorithm based on an unsupervised clustering strategy to address the low complexity implementation issues in multitask networks. Each node adaptively adjusts the combination weight coefficients by minimizing the instantaneous mean square deviation (MSD) in frequency-domain. The simulation results demonstrate that the proposed algorithm achieves superior performance.

引用

页码：1640 / 1644

页数：5

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