matlab-3

信道估计中所使用的关键程序希望对大家有帮助(Channel estimation used in the critical processes for all of us want to help)

是希尔伯特黄变换的matlab程序，很有用，尤其对于初学者，有问题可以和我联系，呵呵(it is for easy for the beginner)

particle filtering RBPF in matlab

说明：  压缩文件夹中包含二十几个ＭＡＴＬＡＢ编写的仿真程序，包括ＧＭＳＫ信号的调制仿真，ＰＮ码生成，ＦＩＲ滤波器的设计，ＧＯＬＤ序列的生成等等，另外还有许多经典的滤波器变换的小程序(compressed file folder containing 20 prepared by several MATLAB simulation program, including GMSK modulation signal simulation, PN code generation, FIR filter design, GOLD sequence generation, etc., in addition to many classic filter transform small program)

matlab用于散点插值的程序代码，为克里金插值算法，代码全，有很大的参考性(matlab program code for scattered point interpolation, kriging interpolation algorithm, code-wide, there is a lot of reference)

Digital Bandpass Transmission(Digital Transmission)

主要介绍了matlab软件中的画图语句，便于大家参考学习(Matlab software drawing statements for easy reference learning)

超宽带定位系统，较好的一本书，涉及很多方面的内容(Ultra-wideband positioning system, a good book, involving many aspects)

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)

code producing figure 1.12 of the book "informatioin theory,inference,and learning algorithm"