paper2

code to find different FFTs.

说明：  LIBSVM是台湾大学林智仁(Lin Chih-Jen)副教授等开发设计的一个简单、易于使用和快速有效的SVM模式识别与回归的软件包，他不但提供了编译好的可在Windows系列系统的执行文件，还提供了源代码，方便改进、修改以及在其它操作系统上应用；该软件还有一个特点，就是对SVM所涉及的参数调节相对比较少，提供了很多的默认参数，利用这些默认参数就可以解决很多问题；并且提供了交互检验(Cross Validation)的功能。(LIBSVM Taiwan University, Lin Zhiren (Lin Chih-Jen) and associate development and design of a simple, easy to use and fast and efficient SVM pattern recognition and regression of the package, he can not only provide a compiled implementation of the system in the Windows family of documents , also provides the source code to facilitate the improvement, modification and other operating systems applications the software has a feature that the parameters of the SVM involves relatively small adjustment to provide a lot of default parameters, use the default parameters on can solve many problems and to provide a cross-validation (Cross Validation) feature.)

基于模糊数学的模识别，，程序比较实用，，希望对大家有帮组(Model identification based on fuzzy mathematics, the program more practical, we hope to have help group)

有限反馈的仿真程序，当选择不同的发送用户数时候的系统吞吐量。(Limited feedback simulation program, when choose a different number of users when sending the system throughput.)

lleach code under mathab for the simulation

应用最小二乘法对二阶加零点系统进行辨识，得到相关参数(Least square method a second order zero system identification, are relevant parameters)

the attached all programs are based on error control coding for ex. LBC, Convolition, RS code etc. all programs are generalized means for any size input or any type of circuit respectively. the all programs are tested on matlab 2012

数学应用中的25个matlab程序，绝对经典，对初学matlab编程有很好的参考价值。(Mathematical applications in matlab program 25, an absolute classic, matlab programming for beginners have a good reference value.)

聚类的MATLAb代码程序~此代码实现的为K均值聚类~(Clustering MATLAb code- This code implements the program for K-means clustering ~)

经验正交函数分析方法，是一种分析矩阵数据中的结构特征，提取主要数据特征量的一种方 法。常用于海洋、气象专业。(Empirical orthogonal function analysis method is an analysis of the data structure of the matrix, a method of extracting the main characteristics of the data volume. Commonly used in the marine, meteorology profession.)