finchart

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))

综合粒子群和蚁群算法，再利用免疫算法中交叉变异算子；形成ACO-AIA-PSO混合算法，求解TSP问题(Integrated particle swarm and ant colony algorithm, and then use the crossover operator and mutation operator of immune algorithm the formation of ACO-AIA-PSO hybrid algorithm, for solving the TSP problem )

ann The models used in MPC are generally intended to represent the behavior of complex dynamical systems. The additional complexity of the MPC control algorithm is not generally needed to provide adequate control of simple systems, which are often controlled well by generic PID controllers. Common dynamic characteristics that are difficult for PID controllers include large time delays and high-order dynamics.

MIMO-OFDM的实现，不同点数的OFDM的实现以及SISO 和 MIMO之间的性能对比。(Implementation of MIMO-OFDM, OFDM, and the realization of the performance comparison of different points between SISO and MIMO.)

几个数据拟合的例子，比较简单，供大家学习。(Several examples of data fitting, relatively simple for everyone to learn.)

FMCW调频连续波雷达的测距测角，本程序的性能已经超过其他算法，合成孔径雷达（SAR)目标成像仿真。( FMCW frequency modulated continuous wave radar range and angular measurements, This program has exceeded the performance of other algorithms, Synthetic Aperture Radar (SAR) imaging simulation target.)

手指静脉 ROI 感兴趣特征区域 提取 matlab实现(Finger vein ROI feature regions of interest extraction matlab achieve)

计算hht 谱分析matlab 程序，仅供参考(hht spectral analysis program for matlab)

说明：  License from matlab 2017a

说明：  英文书《Digital Signal Processing with Examples in MATLAB》附带的MATLAB实例(English book )