Roscoe-PMU

双十字阵矢量水听器阵的指向性研究，自己写的，试试看(double ten is written by me)

matlab codes in communication lab 1

matlab实用程序百例2 很实用的 对初学者大有裨益(Matlab program the practical example 2 is very useful for beginners greatly )

自己在网上看到的一个关于平方根的求值方式，可以参考下(Themselves in line to see a square root to be evaluated on, you can refer to the following)

simulink环境下的双极性PWM控制的单向电压型整流器的模型(simulink environment bipolar PWM control unidirectional voltage source rectifier model)

说明：  实现特征波长的提取，连续投影算法可以实现特征光谱信息，结合PCA实现样品分类(Realize the extraction of characteristic wavelength)

说明：  HUFFMAN 编码 主要针对于灰度图像(HUFFMAN coding focused on the gray image)

信号分为同相信号和正交信号，分别进行正交采样，降低采样率，搬移频带，完成采样。(Signal into in-phase signal and the quadrature signal, respectively, quadrature sampling, the sampling rate decrease, moving band, complete sampling.)

MATLAB编程 谐波信号的现代谱估计算法实现[必做] 采用Matlab编程 [可以利用MATLAB的本征分解函数] (MATLAB)

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)