btreeP

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)

随机场的模拟（利用解析解模拟参数的随机场，markov自相关函数）(analytical simulation of random field)

MIT归一化算法，为了克服MIT自适应律的缺陷需要对其做些修正，使得自适应增益与输入信号幅值无关(MIT normalization algorithm, MIT adaptive law in order to overcome its shortcomings need to do to fix such adaptive gain is independent of the input signal amplitude)

是小学期课程设计的题目，ofdm系统仿真 含16qam调制 fft 加窗 加cp等模块，小波包分析提取振动信号中的特征频率。( Is the topic of the elementary school stage curriculum design, ofdm system simulation including 16qam modulation fft windowing modules plus cp, Wavelet packet analysis to extract vibration signal characteristic frequency.)

说明：  it is a part of a genetic algorithm applied to image segmentation

matlab和delphi的混合编程让你在轻松搞定界面的时候也轻松搞定计算(matlab and mixed delphi programming allows you to easily get in when the interface easy to get the calculation)

说明：  雷达信号理论的分析工具及其matlab 仿真， 可供学习使用。(Analysis tools for radar signals theory and mtlab simulink)

svm分类器，有几类样本点，利用线性SVM分类器求出其分界面(svm classifier, there are several types of sample points, using a linear SVM classifier obtained the sub-interface)

求给定初值问题的数值解 用了龙格库塔和欧拉发解的(Demand for a given initial value problem with the Runge-Kutta numerical solution and the solution of the Euler made)

matlab代码 图像处理中基于ROF的去噪 求解ROF(denoising ROF)