save_dx

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))

in this file wrote digital modulation function for about all digital modulation

双馈电机matlab中的仿真模型文献，有风力机的介绍(Modeling and Simulation of Doubly—Fed Induction Wind Power System Based on Matlab／Simulink)

matlab实现GPS跟踪中kalman滤波的应用(matlab realize GPS tracking kalman filtering applications)

Implementing Class Constant Filter Source Code for Andriod.

这是用牛顿迭代法求解的关于多元二次非线性方程组的MATLAB程序，正确无误，本人在使用，无误(This is about multiple quadratic nonlinear equations MATLAB program Newton iterative method, and correct, I would use, correct)

关于采样数据得频谱分析MATLAB事例程序(Sampling data on a spectral analysis program MATLAB examples)

模糊聚类的经典算法，可以使用UCI数据集进行聚类，该程序附有详细的说明(Classical fuzzy clustering algorithm, you can use the UCI data sets clustering, the program is accompanied by a detailed description of)

用户个人信息的设计题,将姓名,性别,生日,爱好记录在TextArea中,只是一个小程序而已.(The design problem, the personal information of the user s name, gender, birthday, interest is recorded in TextArea, only a small program. )

一种改进的萤火虫算法解决动态0-1背包问题。经过测试，算法就有良好的性能。(Firefly Algorithm (FA), Genetic Algorithm (GA) and Differential Evolution (DE) have been widely used for static optimization problems, but the applications of those algorithms in dynamic environments are relatively lacking. In the present study, an effective FA introducing diversity with partial random restarts and with an adaptive move procedure is developed and proposed for solving dynamic multidimensional knapsack problems. To the best of our knowledge this paper constitutes the first study on the performance of FA on a dynamic combinatorial problem. In order to uate the performance of the proposed algorithm the same problem is also modeled and solved by GA, DE and original FA. Based on the computational results and convergence capabilities we concluded that improved FA is a very powerful algorithm for solving the multidimensional knapsack problems for both static and dynamic environments.)