BER-for-BPSK-in-AWGN

目标跟踪中航迹关联算法，二维分配，三位定位(Track correlation algorithm for target tracking, two-dimensional distribution)

matlab信号处理，很详细的一本书，希望对你们有所帮助(matlab signal processing, a very detailed book, want to help you)

盲分离算法，处理声音信号的分离，供语音识别使用(Blind separation algorithm, which handles the separation of sound signals, is used for speech recognition.)

This code is used for trajectory tracking using Kalman filter.

very useful book about MIMO-OFDM wireless communications with matlab

实现在任意格式的图片中隐藏信息 联合开发网 - pudn.com

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802.11完整OFDM仿真程序，包括发送端和接收端，调制及解调(OFDM simulink code)

全面分析机械类个企业的经济效益，以一家公司的盈利额为研究对象，选择了8个不同的利润指标，14企业关于这8个指标的统计数据如下表所示，试进行主成分分析。(Comprehensive analysis of the economic efficiency of enterprises machinery months to a company' s earnings amounted research object, select 8 different profit targets, 14 companies on these eight indicators of statistical data in the following table and try to principal component analysis.)

feature selection algorithm