kuaisufuliyebianhuan

分层空时码的自己编写的zf分解检测程序，包括判决无误和判决有误差两种情况(Layered space-time codes zf prepared by decomposition of their own testing procedures, including the accurate judgments and sentences a margin of error of two cases)

阵列超声阵列个数对D的影响，仿真图显示对比(array of ultrasonic array number of D simulation chart shows the contrast)

通过matlab仿真对多种不同的盲均衡算法收敛性能进行了比较(By matlab simulation for a variety of different blind equalization algorithm compares the performance of convergence)

说明：  站内搜到一个stegerwarming但是运行不出来，传一个自己写的请批评指正(I found a steger-warming programme on the site, but it didn't work out. Here's my work on this. Please criticize and correct me)

本文简单介绍了matlab神经网络工具箱应用并附有例子(This article explains the application of neural network toolbox matlab together with examples)

在小波分析及其变换中，Hurst指数的Matlab实现(Wavelet analysis and transformation, Hurst exponent of Matlab achieve)

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)

基于MATLAB信号与系统的GUI界面开发,详细讲解了信号系统和GUI Matalb的使用，并有详细例子。特别好！(GUI interface development system based on MATLAB Signal and gave a detailed account of the signal system and GUI Matalb use, and detailed examples. Particularly good!)

基于Matlab语言的Monte_Carlo入门教程.用于初学者学习。有一定的指导意义。(Based on Matlab language Monte_Carlo Tutorial. For beginners. Have some significance.)

用编写的集机器人设计、分析、仿真与一体的软件，非常有工程使用价值，完全可用！(prepared with the set robot design, analysis, simulation and integration software, it works very useful and it is perfectly possible!)