AntSystem

在读入一个图像时，使用量化矩阵对图像做量化(In reading an image, use images to do quantitative quantization matrix)

说明：  SUSAN边缘检测的Matlab实现代码，用于静态图象的边缘检测，效果要视具体图象来定(SUSAN Edge Detection Matlab code for static images of edge detection, the effect would depend on the specific images to determine)

Matlab GUI 初学者视频教学2，非常实用的视频教学文件(Matlab GUI2 learner video teaching,very useful)

SERPSK SERPAM SERQAM

How to run windows media player activex in matlab

子空间匹配追踪源代码。matlab实现的函数。是学习压缩感知的入门资料。(this is a matlab code of subspace pursuit algorithm .which is helpful to study CS.)

这是关于蓝牙跳频通信系统的仿真设计，利用MATLAB的SIMULINK仿真模型，分为跳频系统传输部分、FH-CPM Modulaor子系统、信号接受部分、FH-CPM Demulator子系统、Dis-assemble Packet子系统、频谱分析模块、误码分析模块共七个模块，共有6个MDL文件。(This is about the Bluetooth frequency hopping communication system simulation design, the use of MATLAB-SIMULINK simulation model is divided into frequency-hopping system transmission parts, FH-CPM Modulaor subsystem, signal receiving part, FH-CPM Demulator subsystem, Dis-assemble Packet sub- system, spectral analysis module, the error analysis module of seven modules, a total of six MDL file. )

用Matlab实现的孔洞填充算法，可实现类似Matlab imfill函数的功能，填充图像小孔洞(With hole filling algorithm implemented in Matlab, Matlab imfill function can achieve similar functionality,filling small holes in the image.)

GAMS是一款强大的数学优化计算软件。本文件包含三本GAMS与MATLAB,EXCEL及其他数据库的交互的电子教程，包括：Interfacing_with_GAMS.pdf；Linking_Matlab_and_GAMS_A_Supplement.pdf；MATLAB_and_GAMS.pdf(GAMS is a powerful mathematical optimization software. This document contains three electronic tutorial GAMS interact with MATLAB, EXCEL and other s, including: Interfacing_with_GAMS.pdf Linking_Matlab_and_GAMS_A_Supplement.pdf MATLAB_and_GAMS.pdf)

SVM方法的基本思想是：定义最优线性超平面，并把寻找最优线性超平面的算法归结为求解一个凸规划问题。进而基于Mercer核展开定理，通过非线性映射φ，把样本空间映射到一个高维乃至于无穷维的特征空间（Hilbert空间），使在特征空间中可以应用线性学习机的方法解决样本空间中的高度非线性分类和回归等问题。svm 程序，即支持向量机的代码。(The basic idea of SVM method are: the definition of the optimal linear hyperplane, and the search algorithm for optimal linear hyperplane by solving a convex programming problem. Then based on Mercer nuclear expansion theorem, through a nonlinear mapping φ, the sample space is mapped to a high-dimensional and even infinite dimensional feature space (Hilbert space), so that in the feature space can be applied to solve the linear learning machine method, the sample space The highly nonlinear classification and regression problems. svm procedures that support vector machine code.)