French-DeGroot社会网络模型的结构辨识与参数估计

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	French-DeGroot社会网络模型的结构辨识与参数估计
其他题名	Structure inference and parameter identification for French-DeGroot type of social networks
	董艳萍 1; 任晓涛 1; 赵文虓 1
	2019
发表期刊	控制理论与应用
ISSN	1000-8152
卷号	36.0 期号:011 页码:1905-1911
摘要	近年来社会网络的研究受到越来越多的关注.本文研究基于French-DeGroot模型的社会网络参数和结构辨识问题,通过网络中个体所持的观点来判断个体间是否存在影响关系、进一步估计个体之间影响的大小.具体而言:假设网络存在固执个体(stubborn agents)和非固执个体(non-stubborn agents)两类,当固执个体的观点为零均值独立同分布随机变量序列时,利用最小二乘算法估计网络未知参数,证明了估计的强一致性并给出收敛速度;进一步,构造结构辨识算法判断个体间是否存在影响关系,证明了结构辨识算法的有限时间收敛性.最后给出仿真例子验证算法的有效性.
其他摘要	In recent years, the research on social networks has attracted much attention. In this paper we consider the parameter and structure identification of social networks based on the French-DeGroot model. We assume that there are two types of agents in the network, i.e., stubborn agents and non-stubborn agents. Based on the assumption that the opinions of the stubborn agents are a sequence of independent and identically distributed random variables with zero expectation, the parameter matrix of the French-DeGroot model is recursively estimated by the least-square algorithm, and strong consistency of estimates as well as convergence rate are established. Then structure identification algorithm for the network is proposed and it is proved that with the estimates we can infer the structure of the network, i.e., whether mutual influence existing between agents can be exactly identified with finite number of observations. Finally, numerical examples are given to testify performance of the algorithms.
关键词	社会网络最小二乘算法参数估计结构辨识
收录类别	CSCD
语种	中文
CSCD记录号	CSCD:6645567
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/53119
专题	中国科学院数学与系统科学研究院
作者单位	1.中国科学院数学与系统科学研究院 2.中国科学院大学
推荐引用方式 GB/T 7714	董艳萍,任晓涛,赵文虓. French-DeGroot社会网络模型的结构辨识与参数估计[J]. 控制理论与应用,2019,36.0(011):1905-1911.
APA	董艳萍,任晓涛,&赵文虓.(2019).French-DeGroot社会网络模型的结构辨识与参数估计.控制理论与应用,36.0(011),1905-1911.
MLA	董艳萍,et al."French-DeGroot社会网络模型的结构辨识与参数估计".控制理论与应用 36.0.011(2019):1905-1911.