Classi

信道自适应盲均衡算法源码，调试通过，感兴趣的下来试试。(blind adaptive channel equalization algorithm source code, debugging passed, the interest down try.)

my project in simulating 4g network LTE and LTE-Advanced

说明：  均值类恒虚警检测器（ML-CFAR），包含了平均检测器（CA-CFAR）和最值检测器（GO-CFAR和SO-CFAR），运算速度快，非常适合于单目标的检测(detectors based on mean level constant false alarm rate (ML-CFAR))

说明：  SIMULINK教程，内含大量实例，由简入繁，轻松快捷掌握(SIMULINK Tutorial, containing a large number of examples, from simple to complex, quick and easy to master)

程序采用显示方案实现“平均曲率运动(MCM)”的模型，解法为显示解(Program implementation by show "mean curvature motion (MCM)" model, solution for display solutions )

算术编码源代码，可以编码一个字母序列，字母范围为a，b，c，e，d，( the root code of arithmatic coding ，very simple )

数据统计与分析【matlab例程】经典算法直接应用方便快捷(Statistics and data analysis routines convenient [] classical algorithm matlab direct application)

说明：  上转型对象 1．实验目的 掌握上转型对象的使用。 2． 实验要求 要求有一个abstract类，类名为Employee，Employee的子类有YearWorker、MonthWorker和WeekWorker。YearWorker对象按年领取薪水，MonthWorker按月领取薪水，WeekWorker按周领取薪水。Employee有一个abstract方法： public abstract earnings() 子类必须重写父类的earnings()方法，给出各自领取薪水的具体方式。 有一个Company类，该类用Employee数组作为成员，Employee数组的单元可以是YearWorker对象、MonthWorker对象或WeekWorker对象的上转型对象。程序能输出Company对象一年需支付的薪水总额。 (The transformation of the object 1. Purpose of the experiment used to grasp the transformation of the object. 2. Experiment requires a abstract class requirements, class named Employee, Employee of the child class has YearWorker, MonthWorker and WeekWorker. YearWorker object to receive annual salary, MonthWorker receive a monthly salary, WeekWorker receive weekly salary. Employee one abstract method: public abstract earnings () sub-class must override the parent class of earnings () method, given their own specific way of receiving pay. A Company class, such as members with an array of Employee, Employee of the array elements can be YearWorker object, MonthWorker object or objects on the transformation of objects WeekWorker. Company object program can output a year' s salary to be paid the total amount.)

基于遗传算法，进而优化惩罚因子，核函数参数的的支持向量机进行分类(GA SVM classification)

说明：  这个是矢量控制，对三相异步电动机，仿真结果是正确的(This is vector control. For three-phase asynchronous motor, the simulation result is correct)