AdaboostROC

code to draw hexagon cells in matlab

PID tuning cruise control

模拟一群鸟捕食的情景，从而达到优化目标函数的目的，这就是粒子群算法！起初在可行的空间中随机的产生一群粒子，然后让每个粒子开始在虚拟的空间中向四面八方飞翔，并且每个粒子都记下他们飞过的适应值（也就是目标优化函数）最高的点，而且整个粒子群有一个最高适应值个体，这样，粒子在飞翔的时候尽量朝向自己曾飞过的最好的点和集体的最好的点。最后达到收敛到近似最优点的目的。 (Simulation of a group of birds preying on the scene, so as to achieve the purpose of optimizing the objective function, that is, PSO! At first, where feasible, have a space in a group of random particles, and then let the beginning of each particle in a virtual space to fly in all directions, and each particle they have in mind over the fitness value (that is objective optimization function) the highest point , and the whole particle swarm adaptation has a maximum value of the individual, so that particles in the fly when he had flown as far as possible towards the best point and collective best point. Finally reaching the merits of convergence to approximate most purposes.)

改进的模拟退火算法，求解TSP问题，增加了升温过程，算法效果好。(Improved simulated annealing algorithm for TSP, increasing the heating process, a good algorithm results.)

局部二进制模式，LBP，是已被用于纹理特征的一个 分类。在本文中，提出了一种基于使用这些功能的方法 检测缺陷图案的面料。在培训阶段，在第一个步骤LBP算子是 施加到无缺陷织物样品，逐个象素和参考的所有的行（列） 特征矢量的计算。那么这个图像被分为Windows和LBP算子是 应用这些窗口的每一行（列）。根据与参考比较 特征向量一个合适的阈值，无缺陷的窗户被发现。在检测阶段中，一个 测试图像被划分成的窗户，并使用阈值时，有缺陷的窗口可以 检测到。该方法简单，灰度不变。由于其简单性， 线上实现是可能的。(Local Binary Patterns, LBP, is one of the features which has been used for texture classification. In this paper, a method based on using these features is proposed for detecting defects in patterned fabrics. In the training stage, at first step LBP operator is applied to all rows (columns) of a defect free fabric sample, pixel by pixel, and the reference feature vector is computed. Then this image is divided into windows and LBP operator is applied to each row (column) of these windows. Based on comparison with the reference feature vector a suitable threshold for defect free windows is found. In the detection stage, a test image is divided into windows and using the threshold, defective windows can be detected. The proposed method is simple and gray scale invariant. Because of its simplicity, online implementation is possible as well. )

在此模型中我们首先研究基于高斯隐藏马尔科夫随机字段 （HMRF） 模型及 expectationmaximization (EM) 算法。然后我们概括它到以混合物基于模型的隐马尔科夫随机字段。在 MATLAB 中实现的算法。我们也应用该算法对彩色图像分割问题和 3D 体积分割问题. 马尔科夫随机字段 （集控） 已被广泛应用计算机视觉问题，例如图像分割曲面重构和深度推理。 太多的高效算法，其成功属性如迭代条件模式和对"数据信"和"模型平滑"的审议.第一次的脑部 MR 图像分割方法提出了HMRF EM 框架。为简单起见，我们第一次认为该图像是二维灰度级和强度的每个区域对其进行分段分布服从高斯分布。给出了图像 Y = （y

matlab图形图像处理教程2，我用过，很不错的资料(matlab image processing tutorial 2 graphics, I used, very good information)

CRC 循环冗余校验码 matlab 实现(CRC cyclic redundancy check code)

资料中介绍了几种经典信噪比估计算法的编码并进行比较，包括误差矢量幅值法、最大似然估计、迭代法以及奇异值分解法。(Data introduces several classical coding SNR estimation algorithm and compared, including error vector magnitude, maximum likelihood estimation, iterative method and singular value decomposition.)

matlab 的一些2D动画集合，都是都是一些纯代码的没有GUI图片之类的(matlab collection of some of the animation are pure code are some pictures of the class without a GUI)