MTL_FDTD

首先从n个数据对象任意选择 k 个对象作为初始聚类中心；而对于所剩下其它对象，则根据它们与这些聚类中心的相似度（距离），分别将它们分配给与其最相似的（聚类中心所代表的）聚类；然后再计算每个所获新聚类的聚类中心（该聚类中所有对象的均值）；不断重复这一过程直到标准测度函数开始收敛为止。一般都采用均方差作为标准测度函数. k个聚类具有以下特点：各聚类本身尽可能的紧凑，而各聚类之间尽可能的分开。(First, a data object from the n choose k objects as initial cluster centers and for the rest of the other objects, according to their similarity with the cluster center (distance), respectively, assign them to their most similar (represented by cluster center) clustering then calculated for each cluster center received a new clustering (all objects in the cluster mean) repeats this process until the convergence criteria begin until the measure function. Standard deviation is generally used as a standard measure function. K a cluster has the following characteristics: the cluster itself as a compact, but separated as much as possible between each cluster.)

多维K-means聚类：空间数据分析中最常用的是聚类分析,而K-MEANS算法是聚类分析中常用的,其主要思想是在给定的聚类数目下对多维(我做的是三维空间点)向量进行聚类(aClus.Center.x=m_vecExtreCenter[i].extrePoint.x; aClus.Center.y=m_vecExtreCenter[i].extrePoint.y;)

hystrysis simulink model

KSVD原始算法：信号稀疏表示中的过完备字典的学习算法(KSVD original algorithm: Signal Sparse Representation of the learning algorithm over-complete dictionary)

this is matlab code to solve various cgsolve problem!!!

说明：  和声搜索算法，进行参数改进，并且对程序的模块做细致的说明(Harmony search algorithm, carry on the improvement of parameters, and the program module for detailed instructions )

用matlab开放环境实现了对数据的非线性回归，方便好用，直接将数据输入到程序中，便可以实现对数据的非线性回归(Open environment with matlab realize the non-linear regression of data, easy to use, enter data directly into the program, you can achieve non-linear regression of the data)

接收端自适应均衡器的LMS算法MATLAB仿真实现(Receiver adaptive equalizer of LMS algorithm MATLAB simulation)

adaptive MMSE equalizer

调制方式的matlab仿真程序，使用matlab2008编写(Modulation matlab simulation program, to use matlab2008 to write)