spiderfun

说明：  使用遗传算法解决函数优化（使用谢菲尔德遗传算法工具箱）(Using genetic algorithms to solve function optimization (using Sheffield genetic algorithm toolbox))

MATLAB CODE FOR POWER FLOW 1

无线传感器网络仿真LEACH协议，希望有人能改进下(Wireless sensor network simulation LEACH protocal, under the hope that someone can improve)

数值解法 例1 用改进的欧拉方法求一阶方程初值问题的 数值解 例2 数学摆的运动方程与近似方程数值解比较 例3 四阶龙格库塔公式求数值解 Matlab实现求数值解 例1 求初值问题y =x*sin(x)-y,y(0)=0的数值 解.先编辑一个定义方程的ODEF函数文件 ODEfun1.m. 例2 求方程组初值问题的数值解,按指定步长 0.05划分节点. 例3 按指定的精度求高阶方程初值问题的数值解.(Numerical Solution of the law a method of using the improved Euler' s equation of order to a first-order initial value problem of the numerical solution of cases of two mathematical pendulum equations of motion compared with the approximate numerical solutions of equations of three cases of fourth-order Runge-Kutta numerical solution of the formula Matlab order to achieve the numerical solution of demand cases seeking an initial value problem y ' = x* sin (x)-y, y (0) = 0 the numerical solution. first, the definition of an equation editor ODEF function file ODEfun1.m. cases of two demand equations initial value problem of numerical solution, according to the specified division of the node step 0.05. Example 3 according to the specified precision of seeking higher-order equation of the numerical solution of initial value problem.)

本文介绍在研究生阶段研究的最新卷积程序，希望有用。(This article describes the stages of postgraduate study at the latest convolution process, seek to help.)

turbo编码源代码！！！！！！！！！！！！！！！！！！！！！！！！！！(turbo coded source code)

matlab gui程序，可以通过选择不同类型，在窗口中显示不同的图形显示内容(a matlab gui program, it can display five kind of pictures)

GM8126 Simple IPCAM demo source code

CSTR 系统仿真代码，用于故障诊断产生模拟数据(CSTR model)

K最邻近密度估计技术是一种分类方法，不是聚类方法。 不是最优方法，实践中比较流行。 通俗但不一定易懂的规则是： 1.计算待分类数据和不同类中每一个数据的距离（欧氏或马氏）。 2.选出最小的前K数据个距离，这里用到选择排序法。 3.对比这前K个距离，找出K个数据中包含最多的是那个类的数据，即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering method. It is not the best method, but it is popular in practice. Popular but not necessarily understandable rule is: 1. calculate the distance between the data to be classified and the data in each other (Euclidean or Markov). 2. select the minimum distance from the previous K data, where the choice sorting method is used. 3. compare the previous K distances to find out which K data contains the most data of that class, that is, the class to which the data to be classified is located.)