MYwhile

实现聚类K均值算法： K均值算法：给定类的个数K，将n个对象分到K个类中去，使得类内对象之间的相似性最大，而类之间的相似性最小。 缺点：产生类的大小相差不会很大，对于脏数据很敏感。 改进的算法：k—medoids 方法。这儿选取一个对象叫做mediod来代替上面的中心 的作用，这样的一个medoid就标识了这个类。步骤： 1，任意选取K个对象作为medoids（O1,O2,…Oi…Ok）。 以下是循环的： 2，将余下的对象分到各个类中去（根据与medoid最相近的原则）； 3，对于每个类（Oi）中，顺序选取一个Or，计算用Or代替Oi后的消耗—E（Or）。选择E最小的那个Or来代替Oi。这样K个medoids就改变了，下面就再转到2。 4，这样循环直到K个medoids固定下来。 这种算法对于脏数据和异常数据不敏感，但计算量显然要比K均值要大，一般只适合小数据量。(achieving K-mean clustering algorithms : K-means algorithm : given the number of Class K, n will be assigned to target K to 000 category, making target category of the similarity between the largest category of the similarity between the smallest. Disadvantages : class size have no great difference for dirty data is very sensitive. Improved algorithms : k-medoids methods. Here a selection of objects called mediod to replace the center of the above, the logo on a medoid this category. Steps : 1, arbitrary selection of objects as K medoids (O1, O2, Ok ... ... Oi). Following is a cycle : 2, the remaining targets assigned to each category (in accordance with the closest medoid principle); 3, for each category (Oi), the order of selection of a Or, calculated Oi Or replace the consumption-E (Or))

Code for Content based image retrieval

移动通信系统中，卷积码的matlab仿真程序(Convolutional code matlab simulation program)

三相逆变器恒功率并网控制的仿真，包括PI等参数(PQ control)

基于遗传算法与粒子群算法的相机标定程序，值得借鉴(The camera calibration program based on genetic algorithm and particle swarm optimization is worthy of reference)

MATLAB行情软件MatlabTraderGUI V1.0（Beta版本） (MatlabTraderGUI V1.0 by faruto)

一种新的函数拟合方法，在某些问题的近似程度上甚至优于径向基插值和Kriging插值方法(A new function fitting method, even better than the approximate extent of some of the issues radial basis interpolation and Kriging interpolation method)

说明：  利用matlab实现牛顿下山法，便于数值分析计算(matlab niudunxiashan)

基于菲涅尔域的双随机相位编码图像加密方案，利用角谱传播法实现(Based on double random phase encoding Fresnel domain image encryption scheme to achieve the use of angular spectrum propagation method)

基于MATLAB仿真的智能BP算法集合，用于先进控制理论的研究，主要是控制器方面的介绍(BP algorithm based on MATLAB simulation smart collection for the study of advanced control theory, mainly the introduction of the controller)