Convergence rates of discrete-time stochastic approximation consensus algorithms: Graph-related limit bounds | |
Tang, Huaibin1,2; Li, Tao3 | |
刊名 | SYSTEMS & CONTROL LETTERS |
2018-02-01 | |
卷号 | 112页码:9-17 |
关键词 | Consensus Sensor network Martingale difference sequence Stochastic approximation Convergence rate |
ISSN号 | 0167-6911 |
DOI | 10.1016/j.sysconle.2017.12.002 |
英文摘要 | In this paper, we study the convergence rates of the discrete-time stochastic approximation consensus algorithms over sensor networks with communication noises under general digraphs. Basic results of stochastic analysis and algebraic graph theory are used to investigate the dynamics of the consensus error, and the mean square and sample path convergence rates of the consensus error are both given in terms of the graph and noise parameters. Especially, calculation methods to estimate the mean square limit bounds are presented under balanced digraphs, and sufficient conditions on the network topology and the step sizes are given to achieve the fast convergence rate. For the sample path limit bounds, estimation methods are also presented under undirected graphs. (C) 2017 Elsevier B.V. All rights reserved. |
资助项目 | National Natural Science Foundation of China[61522310] ; National Natural Science Foundation of China[61603215] ; China Postdoctoral Science Foundation[2016M601152] ; Young Scholars Program of Shandong University ; Shanghai Rising-Star Program[15QA1402000] ; Shu Guang project of Shanghai Municipal Education Commission ; Shanghai Education Development Foundation[17SG26] |
WOS研究方向 | Automation & Control Systems ; Operations Research & Management Science |
语种 | 英语 |
出版者 | ELSEVIER SCIENCE BV |
WOS记录号 | WOS:000427213000002 |
内容类型 | 期刊论文 |
源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/29847] |
专题 | 中国科学院数学与系统科学研究院 |
通讯作者 | Li, Tao |
作者单位 | 1.Shandong Univ, Sch Microelect, Jinan 250100, Shandong, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China 3.East China Normal Univ, Dept Math, Shanghai Key Lab Pure Math & Math Practice, Shanghai 200241, Peoples R China |
推荐引用方式 GB/T 7714 | Tang, Huaibin,Li, Tao. Convergence rates of discrete-time stochastic approximation consensus algorithms: Graph-related limit bounds[J]. SYSTEMS & CONTROL LETTERS,2018,112:9-17. |
APA | Tang, Huaibin,&Li, Tao.(2018).Convergence rates of discrete-time stochastic approximation consensus algorithms: Graph-related limit bounds.SYSTEMS & CONTROL LETTERS,112,9-17. |
MLA | Tang, Huaibin,et al."Convergence rates of discrete-time stochastic approximation consensus algorithms: Graph-related limit bounds".SYSTEMS & CONTROL LETTERS 112(2018):9-17. |
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