chap2

手轮输入是用MPC07运动控制卡开发出的,希望对初学数控得点帮助(Hand wheel input is used to develop MPC07 motion control card, and hope to get some help beginners NC)

说明：  matlab中ga算法的一个小program，还是挺细致的。(ga in matlab algorithm for a small program, we welcome the added ah ~ ~ ~ ~)

OMAP_MUX_MODE7 | AM33XX_PULL_ENBL | AM33XX_PULL_UP| AM33XX_PIN_OUTPUT

yalmip 较早的外文教程，通俗易懂。(yalmip )

LAS file reading. this is useful for reading of LiDAR data LAS file.this is very useful code.

matlab fiber code done

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)

图像处理PPT，适合初学者，介绍各种图像处理方法(Image processing PPT, suitable for beginners, introducing the various image processing methods)

ML的方法在ofdm中的应用，是最大似然在ofdm中的仿真(ML method ofdm application is the maximum likelihood in the simulation ofdm)

卡尔曼滤波器的仿真例子，小程序，卡尔曼滤波器的仿真例子，小程序，卡尔曼滤波器的仿真例子，小程序，(karman filter , karman filter karman filter karman filter )