JnS_Jean-Francois_Cardoso

本程序利用小波变换实现正常心音信号单子带分解与重构(This procedure to achieve a normal heart sounds using wavelet transform signal decomposition and reconstruction with a list)

matlab的3D制图，源代码下载即可运行(matlab, 3D graphics, source code download to run)

QC-LDPC码编程，围长为8，列重为3，无4环(The program contructs column-weight three girth-eight QC-LPDC codes given row-weight and sub-matrix size. row-weights and sub-matrices sizes are variable.)

LTE系统链路级仿真，里面的程序很详尽，适合初学者。(LTE system link level simulation, inside the program in great detail, suitable for beginners.)

基于鱼群算法的研究，matlab仿真和分析(Based on the study of fish school algorithm matlab simulation and analysis)

CHANNEL ESTIMATION AND PREDICTION MATLAB CODE

利用MATLAB自带的优化工具箱求解,包括数据信息(Built using MATLAB toolbox for solving optimization)

非线性方程组迭代法的matlab实现详细介绍 (Iterative method of nonlinear equations matlab implementation details)

MATLAB中移动通信的仿真的用法，比较基本的，比如信号的产生 加噪等等(MATLAB, the simulation of mobile communications usage, more basic, such as signal plus noise, and so produce)

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)