Discrete-Time Zero-Gradient-Sum Algorithm for Distributed Optimization over Directed Networks

被引：0
|
作者：
Zhao, Xinyi [1 ]
Gao, Weifeng [1 ]
Xie, Jin [1 ]
机构：
[1] Xidian Univ, Sch Math & Stat, Xian 710071, Peoples R China
来源：
PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021) | 2021年
关键词：
Zero-Gradient-Sum; Distributed convex optimizations; Discrete-time; Directed networks; CONVEX-OPTIMIZATION;
D O I：
10.1109/CCDC52312.2021.9602040
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposes a discrete-time Zero-Gradient-Sum (ZGS) algorithm over directed networks. It is used to solve the distributed convex optimization problem, which is involved in distributed learning algorithms over directed networks under the background of big data. The proposed ZGS algorithm converges to the globally optimal solution and achieves exponential convergence, whose validity is proved by both theory and numerical simulations.
引用
收藏
页码：2400 / 2404
页数：5
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