computer-voice-input

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)

多径信道仿真以及产生GOLD序列程序,需要的朋友下来看看,资源互换最总要.(multi-path channel simulation and produce GOLD sequence procedures, and we need to see a friend down, the most fungible resources to the total.)

高阶谱分析工具箱，有常见的参数模模型高阶谱估计，DOA估计与时延估计 (Higher order spectral analysis toolbox, common parameter-mode model of higher order spectral estimation of DOA estimation and delay estimation)

maximum likelihood estimation method can be used to very broad estimation

利用Matlab实现光学系统光线追迹功能(Ray tracing of optical system with matlab)

卡尔曼滤波标准matlab程序，应用很广泛的(Matlab standard Kalman filter procedure, the application of a very wide range of)

包括：1、关于STBC技术在频率选择性信道下的性能分析程序 2、对STBC性能的改进系统：STBC-OFDM系统的性能分析程序(掳 眉脌 篓 拢 潞 1 隆 垄 鹿 脴脫脷STBC 录 录 脢玫脭脷脝渭脗脢脩 隆 脭帽脨脭脨脜渭脌脧脗渭脛脨脭脛脺 脰脦枚 鲁 脤脨貌2 隆 垄 露 脭STBC脨脭脛脺渭脛 赂 脛 陆 酶脧渭脥 鲁 拢 潞 STBC-OFDM脧渭脥 鲁 渭脛脨脭脛脺 脰脦枚 鲁 脤脨貌)

用wavedec2()函数对b1,b2两幅图像进行小波分解, 采用’db1’小波,分解到第三级 融合两幅图像。(With wavedec2 () function b1, b2 the two images were decomposed using ' db1' wavelet decomposition to the third level fusion of two images.)

This function Compute the CIEDE2000 color-difference between the sample between a reference with CIELab coordinates Labsample and a standard with CIELab coordinates Labstd The function works on multiple standard and sample vectors too provided Labstd and Labsample are K x 3 matrices with samples and standard specification in corresponding rows of Labstd and Labsample The optional argument KLCH is a 1x3 vector containing the value of the parametric weighting factors kL, kC, and kH these default to 1 if KLCH is not specified.

对于炼钢炉的终点温度和含碳量的预测模型，支持向量机的算法实现。(For steelmaking furnace temperature and the carbon content of the end of the forecast model, support vector machine algorithm.)