调试过的采用CbCr椭圆聚类算法matlab例程

数字图像相位相关性，对两幅图像位移的前后相位变化进行检测(Phase Correlation)

这是一个用liblinear进行分类的例子，需要有liblinear环境(Using liblinear to do classification task)

ICP version 2. Removes one to many correspondences.

利用matlab进行转台法isar成像仿真(isar image)

基于horn-schunck算法的matlab源代码；其中输入一个视频可以用这一算法计算出u和v；即在x和y方向上的速率； (Algorithm based on horn-schunck matlab source code enter a video in which the algorithm can be used to calculate the u and v that x and y directions in the rate )

MATLAB综合教程.rar(comprehensive directory. Rar)

其实popupwindow用起来比Dialog 方便，因为dialog一切都需要你自己来实现，而popupwindow帮我们实现了很多，我认为在使用的时候关键我们要看清参数： popupWindow.showAtLocation(parent, gravity, x, y) parent这个是一个父view试图， gravity 这个默认是居中，我们要指定显示方式：Gravity.LEFT | Gravity.TOP 最后两个参数就是显示的坐标位置，这样就可以根据需求自己定位显示位置了

分析了支持向量回归机在能源需求预测中的优势,确定了输入向量集合和输出向量集合,建立了基于Matlab技术的SVR能源需求预测模型.对我国1985-2008年能源需求相关数据进行模拟与仿真,并对中国2010年和2020年能源需求量进行预测.研究结果表明:一是中国未来对能源的需求量逐渐增加,从2010年的330400万吨标准煤上升到2020年418320万吨标准煤,年均增长率为2.39％；二是在解决我国能源系统小样本.非线性及高维模式识别问题中SVR比BP神经网络等方法有更高的预测精度.(Support vector regression analyzes advantage in energy demand forecast to determine the set of input vectors and output vector set, established SVR energy demand forecasting model based on Matlab technology. Energy demand for our 1985-2008 related data modeling and simulation , and China in 2010 and 2020 energy demand forecast results show that: First, China s increasing demand for energy in the future, from 3.304 billion tons of standard coal in 2010 rose to 4.1832 billion tons of standard coal in 2020, average annual growth rate of 2.39 second is to solve our energy system small sample nonlinear and high dimensional pattern recognition problem SVR higher prediction accuracy than the BP neural network method.)

this is the program to calculate the symmetrical fault in the three phase power system

说明：  《Hyperspectral Remote Sensing》是一本关于高光谱遥感图像处理与应用的英文经典书籍，对于学习高光谱遥感图像的人员有很大的帮助。(&quot Hyperspectral Remote Sensing&quot is a book on hyperspectral remote sensing image processing and application of the English classics, hyperspectral remote sensing images for learning the staff is very helpful.)