sphmie

使用MATLAB的GUI接口设计一个简单的计算器，实现两个数的基本运算。(Use the GUI interface of MATLAB to design a simple calculator,realizing basic operations of two numbers.)

数字信号处理实验，噪声中正弦信号的经典发频谱分析(Digital signal processing experiments, classic sinusoidal signal noise spectrum analysis hair)

gmsk的matlab实现，可直接运行，自己编写的，请高手指点(GMSK matlab to achieve the direct running, I have written, please expert advice)

pca分类程序，主要用于脑电信号的分类。具有较好的分类精度！(pca classification procedures, mainly for the classification of EEG signals. Has better classification accuracy!)

说明：  很好用 ， 实验过的， 素轻松判定素数数。(sushu)

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)

MATLAB ZF MMSE db.mminnorm.mmatlab，File->Set Path->Add Folder。 db(MATLAB ZF MMSE db.mminnorm.mmatlab, File-)

根据系统的动力学方程m文件和simulink求出系统的平衡点(Based on the system dynamics equation of m documents and simulink the equilibrium point of system)

集中问题解答.ppt 集中问题解答.ppt ( 集中问题解答.ppt )

在AR人脸库上进行DCT变换，使用DCT变换后的图像进行 kernel fisher discriminant analysis,其中kernel 函数可以自己选择(In the AR face database on the DCT transform, using the DCT transformed image kernel fisher discriminant analysis, which can choose the kernel function)