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复杂网络上多数决策过程的特征模式

Eigenmode of Decision-by-Majority Process on Complex Networks
课程网址: http://videolectures.net/eccs07_uchida_edm/  
主讲教师: Makoto Uchida
开课单位: 东京大学
开课时间: 2007-12-14
课程语种: 英语
中文简介:
利用特征模态分析方法研究了复杂网络中意见形成动力学的性质。意见形成动力学模型是由位于复杂网络顶点的类自旋变量按多数决策过程建立的。定义了系统的哈密顿量,并利用几个网络模型构造的邻接矩阵的特征值和特征向量估计了系统的哈密顿量。然后,通过数值计算分析了系统初始状态和最终状态的特征模态。结果表明,初始状态下最大特征向量的大小是产生动力学结果的关键决定因素。证明了用初始状态的特征模态可以估计动力学的最终状态。
课程简介: The nature of opinion formation dynamics in complex networks is investigated using eigenmode analysis. Opinion formation dynamics is modeled by a decision-by-majority process of spin-like variables located at vertices of complex networks. Hamiltonian of the system is defined, and estimated by the eigenvalue and eigenvector of the adjacency matrix constructed from several network models. Then, the eigenmodes of initial and final state of the dynamics are analyzed by numerical studies. It is shown that the magnitude of the largest eigenvector at the initial states are key determinant for the resulting dynamics. It is proved that the final state of the dynamics can be estimated by the eigenmodes of the initial state.
关 键 词: 特征模态; 复杂网络; 动力学; 自旋变量; 哈密顿量; 邻接矩阵
课程来源: 视频讲座网公开课
最后编审: 2019-05-26:cwx
阅读次数: 105