cvx

ImageGallery extends NoSearchActivity implements for Andriod.

实现单个卫星导航仿真，可定位分析出目标物的方位(Simulation for single satellite navigation, can locate the position of the target)

entropy of a signal helps to find the randomness

说明：  在考虑汽车零部件包装箱长、宽、高等三维尺寸的约束下，以配送中心为原点，分派多辆同一规格的货车到n个供应商处取货，最后回到配送中心。本章所构建的三维装载约束下的汽车零部件循环取货路径优化模型要解决的问题是确定循环取货路径，要求充分考虑汽车零部件在货车车厢中的三维装载位置，确保每个供应商处的零部件均能成功装载，尽可能使车辆装载率最大，且所有车辆的总行驶路径最短。(In considering the auto parts box length, width, higher dimensional size constraints to the distribution center as the origin, a multi-vehicle dispatch trucks to the same specifications of the pick n suppliers, and finally back to the distribution center. Auto Parts Pick cycle path constructed three-dimensional loading constraints under chapter optimization model to solve the problem is to determine the circulation pickup path requires full consideration in boxcars loaded in three-dimensional position of auto parts, to ensure that each vendor Parts can successfully loaded, as the vehicle maximum loading rate, and the total of all vehicles traveling the shortest route.)

基于混沌的图像加密，用于MATLAB的图像加密，对图像进行置乱。。。。。。。。。。。。。。。(Chaos-based image encryption algorithm implement by matlab)

数据处理软件，模型优化LINGO软件，数学建模数值优化必备！(data processing)

Combined flood and wind damage scales

说明：  matlab图像处理基础源码 1、jpeg压缩 2、6个基本图像压缩源码 3、小波源码(Matlab based image processing a source, jpeg compression 2,6 basic image compression source 3, wavelet FOSS)

QAM调制的ＭＡＴＬＡＢ程序仿真，思路清晰，既可以学习如何用ＭＡＴＬＡＢ编程，又可以理解通信调制技术！(QAM MATLAB simulation procedures, clear thinking, can learn how to use MATLAB programming, but also to understand communication modulation technology!)

三维点云法向量估计综述由于获取方便、表示简单、灵活等优势，点云逐渐成为常用的三维模型表示方法之一。法向量作为点云必不可少的属性 之一，其估计方法在点云处理中具有重要的位置。另一方面，由于点云获取过程中不可避免的噪声、误差和遮挡，点云中通常含 有噪声、外点和空洞，并且部分采样模型如CAD模型，也会存在尖锐特征，这些都给法向量估计提出了挑战。对当前已有的点云 法向量估计算法进行综述，分析其原理及关键技术，着重分析它们在处理噪声、外点和尖锐特征等方面的能力并给出比较，最后 为未来研究提供了一些建议(The three-dimensional point cloud normal vector estimation summarized obtain convenient, represents a simple, flexible, and becoming one of the methods commonly used three-dimensional model represents the point cloud. Normal vector of one of the as point clouds essential attributes, its estimation method has important position in the point cloud processing. On the other hand, the noise is inevitable in the process to obtain because of the point cloud, error and occlusion, point cloud typically contains noise outside point and empty, and part of the sampling model such as CAD models, there will still be sharp features, which gave the normal vector estimated that presents a challenge. Overview of current existing point cloud normal vector estimation algorithm, analysis of the principle and key technologies, and analyzed their ability to deal with the noise, the outer points and sharp features and gives comparison, and finally provide some suggestions for future research)