Dlgfault

使用小波包变换分析信号的MATLAB程序(The use of wavelet packet transform analysis of signals in MATLAB program)

matlab中cputime函数与进度条联合使用示例(matlab in cputime function used in conjunction with the progress bar example)

用matlab GUI界面，实现成绩查询功能的源代码( the source code of Realization the performance query function by matlab GUI interface)

MATLAB关于汽车制动分析 汽车理论 汽车理论 汽车理论(MATLAB analysis on the brake)

本程序为类人机器人的一个运动学正解程序，非常好的参考程序，可以继续在上面扩充(This program is a humanoid robot kinematics program, very good reference program, you can continue to expand in the above)

电力系统日负荷曲线分析GUI程序。考虑不同类别的用户，以及最大负载值、平均负载在指定的期间内的统计分析。(GUIof power system daily load curve analysis algorithm. Consider the different categories of users, and the maximum load value, the average load over a specified period of the statistical analysis.)

很长的一个例子，说实话，我也看不懂。。这个是同学写的。(An example of a very long, I can honestly say I do not watch. . This is the Student Writing.)

MALTAB 관 련 문 서 -한 글 파 일 입 니 다 .(MALTAB 관 련 문 서-한 글 파 일 입 니 다 .)

一种声音合成的算法研究，可用Matlab方法验证(A sound synthesis algorithm used Matlab method validation)

说明：  珍藏版，可实现，新K均值聚类算法，分为如下几个步骤： 一、初始化聚类中心 1、根据具体问题，凭经验从样本集中选出C个比较合适的样本作为初始聚类中心。 2、用前C个样本作为初始聚类中心。 3、将全部样本随机地分成C类，计算每类的样本均值，将样本均值作为初始聚类中心。 二、初始聚类 1、按就近原则将样本归入各聚类中心所代表的类中。 2、取一样本，将其归入与其最近的聚类中心的那一类中，重新计算样本均值，更新聚类中心。然后取下一样本，重复操作，直至所有样本归入相应类中。 三、判断聚类是否合理 采用误差平方和准则函数判断聚类是否合理，不合理则修改分类。循环进行判断、修改直至达到算法终止条件。(NewK-means clustering algorithm ，Divided into the following several steps: A, initialize clustering center 1, according to the specific problems, from samples with experience selected C a more appropriate focus the sample as the initial clustering center. 2, with former C a sample as the initial clustering center. 3, will all samples randomly divided into C, calculate the sample mean, each the sample mean as the initial clustering center. Second, initial clustering 1, according to the sample into the nearest principle clustering center represents the class. 2, as this, take the its recent as clustering center of that category, recount the sample mean, update clustering center. And then taking off, as this, repeated operation until all samples into the corresponding class. Three, judge clustering is reasonable Adopt error squares principles function cluster analysis.after clustering whether reasonable, no reasonable criterion revisio)