PairsTrading_FEX

基于matlab的简易OCR程序。 具体可参加该文件夹内的CS585 Fall 1998 Project One.....(Simple OCR matlab-based program. May participate in the specific folder within the CS585 Fall 1998 Project One .....)

说明：  毛拉贝库算子的MATLAB实现,用于计算图像的特征点(hair Rabe Operator for the MATLAB used in the calculation of the image feature points)

典型的MATLAB编程实现MSK连续功率谱描述，并且绘出相应的离散点的功率谱值……(The typical MATLAB programming the MSK continuous power spectral description, and draw the power spectral values ​ ​ of the corresponding discrete points ......)

关于matlab fixunknowns函数问题给出我的解答(Give me answers about the issue of the matlab fixunknowns function)

这是信号与系统的matlab教程，基础但实用(This is the signal system matlab tutorial, basic but practical)

通过pch文件提取nastran质量矩阵、刚度矩阵，需要更改文件名称和自由度数（dof）,生成质量矩阵、刚度矩阵M,K(Extraction of mass matrix, stiffness matrix of NASTRAN)

Matlab 与工控组态软件RSView32 的通信设计(Matlab and Industrial Control Configuration Software RSView32 communication design)

Heat Transfer with CRANK NICOLSON Method

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.)

本演示实现了主动轮廓模型由Kass等人提出。 要运行它的图形用户界面 1。基于MATLAB型引导提示。 2。关于“到现有的图形用户界面，点击” 3。选择在与本文件相同的目录snk.fig文件 4。按一下上方的绿色箭头启动图形界面 一旦GUI已经启动，您可以通过使用蛇 1。点击“新形象”，并加载输入图像。提供的样品图像。 2。平滑参数设置“西格玛”或保留其默认值并点击“过滤器”。这将平滑图像。 3。只要你点击“过滤器”，头发会出现交叉，用他们和你左击鼠标，您可以选择在图像上的初始轮廓的位置。会出现一个红色圆圈到处您单击并在多数情况下，你应该单击对象周围的一切你想要的部分。最后一点，必须挑选使用右键单击，以阻止更多的积分为MATLAB的要求。 4。设置各种蛇参数（在能源方面的相对权重的蛇目标函数）或离开它们的默认值，然后按一下他们“迭代”按钮。蛇会出现和移动，因为它收敛到它的低能量状态。(This demo implements the Active Contour Models as proposed by Kass et al. To run it with GUI 1. Type guide on the matlab prompt. 2. Click on "Go to Existing GUI" 3. Select the snk.fig file in the same directory as this file 4. Click the green arrow at the top to launch the GUI Once the GUI has been launched, you can use snakes by 1. Click on "New Image" and load an input image. Samples image are provided. 2. Set the smoothing parameter "sigma" or leave it at its default value and click "Filter". This will smooth the image. 3. As soon as you click "Filter", cross hairs would appear and using them and left click of you mouse you can pick initial contour location on the image. A red circle would appear everywhere you click and in most cases you should click all the way around the object you want to segment. The last point must be picked using a right-click in order to stop matlab for asking for more points. 4. Set the various snake paramete)