Performance Analysis of Compressive Diffusion Normalized LMS Algorithm With Link Noises

被引:2
|
作者
Zhang, Sheng [1 ]
Zheng, Wei Xing [2 ]
机构
[1] Southwest Jiaotong Univ, Sch Informat Sci & Technol, Chengdu 611756, Sichuan, Peoples R China
[2] Western Sydney Univ, Sch Comp Data & Math Sci, Sydney, NSW 2751, Australia
来源
2021 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) | 2021年
基金
澳大利亚研究理事会; 中国国家自然科学基金;
关键词
RECURSIVE LEAST-SQUARES; DISTRIBUTED ESTIMATION; ADAPTIVE NETWORKS; MEAN SQUARES; FORMULATION; STRATEGIES;
D O I
10.1109/ISCAS51556.2021.9401635
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 paper, an investigation is launched into the compressive diffusion strategy in the presence of noisy communication links so as to develop the compressive diffusion double normalized least mean square (NLMS) algorithm. Based on the single update global weight-error model, an analytical formulation of the transient and steady-state results is made for the compressive diffusion double NLMS algorithm. These analytical results are instrumental to making a better understanding of the meansquare performance of the compressive diffusion strategy against link noises. Lastly, simulation study is carried out to validate the performance of the developed compressive diffusion double NLMS algorithm over adaptive networks subject to link noises.
引用
收藏
页数:5
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