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ar算法的matlab源程序的验证，对于随机过程的信号处理有所帮助(ar algorithm matlab source of verification, for random processes signal processing help)

拥有VC界面的KALMAN滤波代码，仿真界面清晰易懂。(KALMAN filter with VC interface code, simulation interface clear and easy to understand.)

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))

用matlab 编写的kalman filter 程序(using Matlab prepared by the Kalman filter process)

Type-2 Fuzzy Logic Toolbox, 土耳其教授MUZEYYEN BULUT OZEK编写的。做simulink仿真有用。(Type-2 Fuzzy Logic Toolbox by Prof. MUZEYYEN BULUT OZEK)

programme de sttc o bien stbc12341

K均值算法，适合于初学者。包括matlab源代码，测试数据等。(K-means algorithm)

判断网络的连通性，网络连通输出1，不连通输出2(Determine the connectivity of the network, network connected output 1, disconnected output 2)

地面上方单导线传输线的单位长度电容的矩量法求解(Ground above the single-wire transmission line capacitance per unit length of the moment method)

covairance code for cr