matlabchengxushiyanquanji

著名的monte carlo 算法，里面详细的介绍了monte carlo 算法的特点。并举了好几个例子来说明该算法的应用。(A very famous monte carlo algorithm. In this article, the characteristics of monte carlo algorithm is introduced. What s more, several applications are presented.)

LOAD FLOW ANALYSIS BY FAST DECOUPLED LOAD FLOW ANALYSIS

this is matlab code for create admittance matrix

讲述了卡尔曼在MATLAB中的应用以及几个样例，可以让读者理解其简单应用(Kalman described in MATLAB, as well as several sample applications that can help readers understand the simple application)

高阶谱工具包，用于计算信号的各阶谱结构，得到信号在高阶谱情况下的重要特征(higher-order spectral toolkit)

介绍了什么是函数文件及如何编写函数文件等等(What is the function of the document describes how to write functions and files, etc.)

说明：  Matlab是Matlab产品家族的基础，它提供了基本的数学算法，例如矩阵运算、数值分析算法，Matlab集成了 2D和3D图形功能，以完成相应数值可视化的工作，并且提供了一种交互式的高级编程语言——M语言，利用M语言可以通过编写脚本或者函数文件实现用户自己的算法。 这是关于matlab的教程(Matlab family of products is the basis of Matlab, which provides the basic mathematical algorithms, such as matrix computation, numerical analysis algorithms, Matlab integrates 2D and 3D graphics features, in order to complete the corresponding numerical visualization work, and provides an interactive high-level programming languages- M language, the use of M language can function through the preparation of the script or document to achieve the user)

分支定界法、割平面法、隐式枚举法的整数规划matlab源代码(The branch and bound method for, cut plane method, the method of implicit enumeration methods of integer programming matlab source code )

The method works as follows. 1. For a data set with dimensionality, d, compute the variance of data in each dimension (column). 2. Find the column with maximum variance call it cvmax and sort it in any order. 3. Divide the data points of cvmax into K subsets, where K is the desired number of clusters. 4. Find the median of each subset. 5. Use the corresponding data points (vectors) for each median to initialize the cluster centers.

逐步判别分析的主函数 用于分类 [sel,c,c0,re,P]=StepclaassV2(data,[50 50 50],data,10) 输入变量 x为训练集.每行为一个样本，每列为一个变量. Class_x,为训练集的分类情况，一行，为各类样本数量,例如[5 6 9] Test为待分类样本. 输出变量：sel为选择的变量序号，c,c0为拟合出的判别函数.re为对Test的判别结果,P为其后验概率. author 王新 2012.4.8 例子Sample: load fisheriris x=meas Class_x=[50,50,50] Test=meas(1:5,:) Fa1=4 [sel,c,c0,re,P]=StepclaassV2(x,Class_x,Test,Fa1)( Stepwise discriminant analysis for the classification of the main function [sel, c, c0, re, P] = StepclaassV2 (data, [50 50 50], data, 10) input variables x as the training set, each conduct a sample of each as a variable. Class_x, the classification for the training set, a row, the number of samples for all types, for example, [5 6 9] Test sample to be classified. output variable: sel for the selected variables serial number, c, c0 is fitted discriminant function. re discrimination results for the Test, P its posterior probability. author Wang 2012.4.8 examples Sample: load fisheriris x = meas Class_x = [50,50,50] Test = meas (1:5, :) Fa1 = 4 [sel, c, c0, re, P] = StepclaassV2 (x, Class_x, Test, Fa1))