An MBSE modeling approach to efficiently address complex systems

该文档介绍了如何在复数域通过有理函数进行插值和逼近。

CMIF - 复杂模式指标函数 输入： H - 全复数 H 矩阵（频率响应函数），包括至少 2 个参考点测量值： 【频点数×DOF数×参考点数】 W - 频率矢量 [Hz] 参考： DJ Ewins，“模态测试：理论、实践和应用”，p。 300

Essential Issues in SOC Design Designing Complex Systems-on-Chip 是SOC设计必备的专业书籍。

for Complex Variables and Applications

Complex Networks Toolbox for MatLab is designed to analyze large-scale graphs, model them, explore with simulations of dynamic processes and generate appealing and insightful layouts. example： function [BetweenneessCentrality, varargout]= GraphBetweennessCentrality(Graph,SourceNodes) % Computes betweenneess centrality of each node. % % Receives: % Graph - Graph Struct - the graph loaded with GraphLoad % SourceNodes - array of double - (optional) nodes, from which passes start. Default: [] (all nodes). % % Returns: % BetweenneessCentrality - array of double - Betweenneess Centrality for each node. % Nodes - array of double - (optional)List of all nodes for which betweennessn centrality is computed % % Algorithm: % http://www.boost.org/libs/graph/doc/betweenness_centrality.html % % See Also: % mexGraphAllNodeShortestPasses % warning('Use the more optimized mexGraphBetweennessCentrality.dll'); error(nargchk(1,2,nargin)); error(nargoutchk(0,2,nargout)); if ~exist('SourceNodes') | isempty(SourceNodes) SourceNodes = unique(Graph.Data(:,1)); end Nodes = unique(Graph.Data(:,1:2)); %TotalPasses = zeros(GraphCountNumberOfNodes(Graph),GraphCountNumberOfNodes(Graph)); Betweenness = zeros(GraphCountNumberOfNodes(Graph),1); for Node = Nodes(:).' [ShortesPasses PassesHistogram]= mexGraphAllNodeShortestPasses(Graph,Node); %TotalPasses = TotalPasses + sum(PassesHistogram(2:end)); tic for i = 1 : numel(ShortesPasses) %T = ShortesPasses(i).Passes(end); %TotalPasses(Node,ShortesPasses(i).Passes(end)) = size(ShortesPasses(i).Passes,2); % compute total number of shortes passes from Node to some other node. Passes = ShortesPasses(i).Passes(2:end-1,:); NodesOnTheWay = unique(Passes); if numel(NodesOnTheWay)==1 Count = 1; % hist behaves differently in this case. else Count = hist(Passes(:),NodesOnTheWay);

真实世界网络分析（复杂网络） 荷兰代尔夫特理工大学复杂网络 - 从自然到人造网络 (ET4389) 课程的最终作业（2013 年） 确定和分析现实世界网络（荷兰足球）的拓扑特性及其物理意义。 此外，研究各种网络模型，如 Erdos-Renyi 随机网络和 Barabasi-Albert 无标度网络。 最后，在研究这些过程下的性能和鲁棒性的同时，对这些网络模型执行诸如渗透、攻击和意见交互等动态过程。 团队成员：Mani Prashanth Varma Manthena、Alon Dolev 作业：[ET4389作业2013](作业/ET4389作业2013.pdf) 报告：[最终作业报告](作业/最终作业报告.pdf)

定义一个名为 的复数类，其属性数据为复数的实部和虚部，要求构造函数和拷贝构造函数，并能打印复数的值

有关复杂变量的本文适用于谁进行了实际分析入门课程。 提供简洁明了的处理方法，可以提供仔细而完整的解释以及许多问题和解决方案。