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Spectral analysis. Analysis, signal coding and voice synthesis in Matlab

掌握Matlab的流程控制语句，掌握循环结构。 初步学习Matlab的脚本文件、函数文件编写。 初步掌握Matlab脚本文件、函数文件的调试.初步掌握用户参数的交互输入。 (Matlab master process control statements, control loop structure. Matlab script file preliminary study, the function document preparation. Initial grasp of Matlab script file, the file' s debugging function. Initial grasp of the user interactive input parameters.)

通过三个具体实例介绍乐MATLAB语言在化学中的应用，说明在数值计算方面其有着比目前流行的高级语言FORTRAN,PASCAL,C无法比拟的强大功能(through three specific examples music MATLAB in chemistry applications, Note the numerical calculation of their share than the currently popular high-level language FORTRAN, and PASCAL. C can not compare with the powerful functions)

基于脉冲电流法的绝缘介质内部局部放电现象仿真。(Partial Discharge simulation based on the Pulse Current detection technology)

matlab实现互现关运算,并采用雅克比——约当法实现逆矩阵的运算，在matlab下测试通过。(Complete correlation and invmaxwith matlab)

The cache manager source code implemented in Windows kernel.

说明：  是冈萨雷斯写的一本关于matlab在图像处理中应用的书籍，介绍了一些基本的方法，值得初学者一看(Is Gonzales wrote a book on applications in image processing matlab books, introduces some basic methods, it is worth a look for beginners)

全新的，自创的m文件，容易理解，容易使用的线性归一化的源代码 (All new,original m-files created by own, easy to understand, easy to use normalization of source code )

matlab gui开发的实用教材 还有一位网友写的初步认识 对想迅速掌握matlab GUI开发的朋友的确有很大的帮助(matlab gui development of practical materials Another netizen wrote an initial understanding of the development to quickly grasp the matlab GUI friend indeed a big help)

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.)