WpfApplication14

说明：  ofdm在matlab的详细实现过程，绝对是可以用的，即帮助你了解算法，也可以直观的看到结果。(OFDM in Matlab detailed implementation process that can definitely be used, which is to help you understand the algorithm can also be intuitive see the result.)

VERY IMPORTANT MATLAB PROGRAM

太阳能电池模型，可以方便的仿真不同温度以及光照下电压，电流以及功率之间的关系曲线(Model of the solar cell, and can facilitate the simulation of the relationship between the different temperatures and light voltage, current, and power curve)

利用VC++6.0集成编程界面编写综合运用MAT数据文件和MATLAB引擎技术的（求矩阵的奇异值）C++源码程序。本程序说明了：1.如何利用VC++6.0集成编程界面编写源码程序；2.编译链接产生EXE文件所需的间夹文件。注意：要将压缩包内除matlabyinqingwithc++.cpp的所有文件都要拷贝到matlabyinqingwithc++.cpp的“任务文件夹下”。(Use VC++ 6.0 integrated programming interface MAT preparation of comprehensive use of data files and MATLAB engine technology (the singular value matrix) C++ Source procedures. This procedure describes: 1. How to use VC++ 6.0 integrated programming interface to prepare source procedures 2. Compiler generated EXE file the necessary link between the document folder. NOTE: In addition to compression packages matlabyinqingwithc++. Cpp must copy all the files to matlabyinqingwithc++. Cpp s mission folder. )

this article is about of target tracking.

HISTOGRAM EQUALIZATION

一款埃及学生用Matlab编的的基于PSO的PID整定程序，使用方法详见程序注释。(Tunning of PID controller using Bacterial Foraging Orientec by Particle swarm optimization My work has been accpepted in GECCO 2008 as Graduat Student workshop. I have used this techique in PID tunning and i got better result thatn BG and PSO Author: Wael Mansour (wael192@yahoo.com) MSc Student, Electrical Enginering Dept, Faculty of Engineering Cairo University, Egypt)

read a file and convert it to binary ,so u can modify it and see ones and zeros

jpeg压缩与解压例子，matlab中离散余弦变换并用huffman编码(jpeg compression and decompression example, matlab and used in the discrete cosine transform coding huffman)

边缘是图像最基本的特征，是图像分割的第一步。经典的边缘检测方法如：Roberts，Sobel，Prewitt，Kirsch，Laplace等方法，基本都是对原始图像中象素的小邻域构造边缘检测算子，进行一阶微分或二阶微分运算，求得梯度最大值或二阶导数的过零点，最后选取适当的阀值提取边界。由于这些算法涉及梯度的运算，因此均存在对噪声敏感、计算量大等缺点。在实践中，发现SUSAN算法只基于对周边象素的灰度比较，完全不涉及梯度的运算，因此其抗噪声能力很强，运算量也比较小。并将SUSAN算法用于多类图像的边缘检测中，实验证明该算法非常适合含噪图像的边缘检测。 2 SUSAN边缘检测简介 (err)