mCode

说明：  簇系数计算函数，复杂网络基本指标。对复杂网络研究者非常有用。(Clustering coefficient calculation functions, complex network of basic indicators. Very useful in complex networks researchers.)

说明：  计算节点功率的失配量，方法简单，便于理解。(Mismatch calculated the amount of power nodes, the method is simple, easy to understand.)

Wiley - Antenna and EM Modeling with MATLAB CHAPTER5

AHP层次分析法源代码，最大程度简化您的计算量(AHP Analytic Hierarchy Process source code, the maximum extent simplify your calculations the amount of)

研究生数值分析课程考试题型的matlab源程序(Graduate numerical analysis course exam questions matlab source)

一种经典MIMO信道模型的仿真程序，对于学习空时信道建模很有用(A classical MIMO channel model of simulation program for studying space-time channel modeling is useful)

Lame波的频散曲线，包括相速度和群速度。(The dispersion curve of Lame wave includes phase velocity and group velocity.)

这是本人用SIMLINK辨析的一个用经典控制理论方法实现的接联惯性导航系统精对准的方法程序。(using SIMLINK Analysis with the use of a classical control theory method of access inertial navigation systems EC precision alignment methods and procedures.)

说明：  1.1 MATLAB软件介绍 1.1.1 MATLAB发展进程 1.1.2 MATLAB的基本功能 1.1.3 MATLAB语言的特点 1.1.4 MATLAB R2011a的新功能 1.2 MATLAB安装与运行 1.3 MATLAB的运行环境 1.3.1 命令窗口 1.3.2 历史命令窗口 1.3.3 工作空间 1.3.4 当前文件夹 1.4 MATLAB帮助文档 1.4.1 帮助窗口 1.4.2 帮助命令 1.5 变量 1.6 矩阵 1.6.1 矩阵创建 1.6.2 数列创建 1.6.3 矩阵的基本运算 1.7 高维矩阵 1.7.1 创建高维数组 1.7.2 高维数组操作函数 1.8 演示MATLAB 1.9 小波分析概述 (1.1 MATLAB Software 1.1.1 MATLAB development process 1.1.2 MATLAB basic functions 1.1.3 MATLAB language features 1.1.4 MATLAB R2011a new feature 1.2 MATLAB installation and operation 1.3 MATLAB runtime environment 1.3.1 Command Window 1.3.2 History Command Window 1.3.3 Workspace 1.3.4 Current folder 1.4 MATLAB help documentation 1.4.1 Help Window 1.4.2 Help Commands 1.5 Variables 1.6 Matrix 1.6.1 Creating Matrix 1.6.2 series created 1.6.3 Basic operation matrix 1.7 high-dimensional matrix 1.7.1 Creating high-dimensional arrays 1.7.2 High-dimensional array manipulation functions 1.8 demo MATLAB 1.9 Overview of Wavelet Analysis )

该算法基本思想是利用一组带有相应权值的随机样本即粒子去逼近PHD分布和基数分布，其意义在于不仅解决重积分计算没有闭式解的难题，而且在滤波过程中，PHD函数被一系列离散的带权值的样本近似，随着样本粒子数量的增加，PHDF接近于Bayes最优估计，而且不受模型线性和高斯假设的限制，可以适用于非线性非高斯的随机系统。(The algorithm the basic idea is to use a set of random sample with the corresponding weight namely particle approximation PHD and base distribution, its significance lies in not only solve the problem of multiple integral calculation without closed solution, and in the process of filtering, PHD function by a series of discrete weighted value of sample approximation, with the increase of sample particles, PHDF close to the Bayes optimal estimation, and is not subject to the assumptions of the linear and gaussian model can be applied to nonlinear non-gaussian stochastic system.)