simulation-of-Diversity-and-MIMO

基于Matlab的现代通信系统的仿真应用 内有SIMULINK通信仿真图(matlab simulink)

说明：  此为C++环境下的LDPC编译码的完整的源代码。常用于通信系统的编译码仿真过程。有助于各种项目的完成。(This is the C++ environment LDPC coding and decoding of the complete source code. Commonly used in the encoding and decoding communication system simulation. Contribute to the completion of various projects.)

.txt文件格式，matlab播放，卡农演奏曲(Txt file format, Matlab player, canon played song)

最小均方濾波器是一類可通過最小化誤差訊號之均方值而修正濾波器係數，以類比所需理想濾波器的自適應濾波器，其中作為修正依據的誤差訊號為理想參考訊號與實際輸出訊號之差。該種濾波器所用之最小均方法只以當前之訊號誤差值為準進行修正，是一種隨機梯度下降法。最小均方法係由斯坦福大學的Bernard Widrow教授及他的首位博士班學生Marcian Hoff於1960年提出。最小均方濾波器屬於常見的自適應濾波器種類之一。(The minimum mean square filter is an adaptive filter that can correct the filter coefficients by minimizing the mean square value of the error signal to analogize the desired ideal filter. The error signal used as the correction reference is the ideal reference signal and the actual output. The difference between the signals. The minimum averaging method used in this kind of filter is only corrected based on the current signal error value, which is a stochastic gradient descent method. The minimum mean method was proposed in 1960 by Professor Bernard Widrow of Stanford University and his first PhD student, Marcian Hoff. The least mean square filter is one of the common types of adaptive filters.)

可有效计算各类熵值，信息熵、样本熵、谱熵计算，与其他程序相似(It can effectively calculate all kinds of entropy, information entropy, sample entropy and spectral entropy, similar to other programs.)

This program calculates the 2D photonic Band Structure with PWE method.

一些雷达公式用matlab来表示 对学习雷达有帮助(Some radar equation using matlab to express learning Radar helpful)

Matlab编写的，利用 SA算法解决VRP问题(Matlab prepared using the SA algorithm to solve the VRP)

飞行器在某高度平飞时舵面偏角和飞行马赫数之间的关系(it describes the relationship between elevator declination and flight mach number，when flight fly on some hight.)

视频背景非参数估计论文及matlab实现.matlab代码只实现了灰度图的背景估计，论文利介绍的彩色视频处理方法可以自己看看怎么做。(Background and Foreground Modeling Using Nonparametric Kernel Density Estimation for Visual Surveillance AHMED ELGAMMAL, RAMANI DURAISWAMI, MEMBER, IEEE, DAVID HARWOOD, AND LARRY S. DAVIS, FELLOW, IEEE Invited Paper )