jackknifeparafac

最小外接矩形，基于最小外切矩形方法来计算目标区域的长宽(Minimum bounding rectangle)

dc motor speed control using fuzzy logic

机构RRR-RRP仿真，里面有仿真模型，M文件(Institutions RRR-RRP simulation, inside the simulation model file)

说明：  使用pca和svm的方法对人脸进行识别和检测，最终达到人脸识别的功能(Face recognition and detection using PCA and SVM methods, and finally achieve the function of face recognition)

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))

通信仿真系统，通过搭建模型，运用此代码产生信噪比与误码率的关系图(Communication Simulation System)

ybus case distributed-generation_distribution-system_Newton-Laphson

make a combination between rectangle and triangle with matlab

基于模糊PID控制下的BUCK电路稳压输出的仿真，并对比了模糊控制和PID控制。(Based on the simulation of BUCK circuit voltage stabilizing output under fuzzy PID control, the fuzzy control and PID control are compared.)

说明：  EMD处理数据的全流程以及经验模态分解的一个经典例子(The whole process of EMD data processing and a classical example of empirical mode decomposition)