mvr61

matlab动态模拟程序，小球的弹性碰撞模拟，直观的展现动态性(matlab dynamic simulation program, a small ball elastic collision simulation, intuitive dynamic display)

采煤机截割滚筒模型，主要包括负载和截割转速牵引速度的关系(Shearer cutting drums of models, including the relationship between the load and speed of the cutting speed traction)

GPS/INS位置组合输出校正Matlab仿真 s_GPS_INS_position_ demo.m 组合主文件 kalman_GPS_INS_position_ NFb.m 卡尔曼滤波程序 ode500.mat 飞机飞行轨迹与INS输出数据 将三个文件放到同一个文件夹中，运行主文件即可。 (GPS/INS Position Combination Output Correction Matlab Simulation S_GPS_INS_position_ demo.m Combines the master file Kalman_GPS_INS_position_ NFb.m Kalman filter procedures Ode500.mat aircraft flight path and INS output data Will be three files into the same folder, run the main file can be.)

note on simulink: intro, description and example

BP neural network trained by PSO algorithm

寻找距离某一点最近的几个点，返回对应的点的位置及距离该点的距离(Find a few points closest to a given point , returns the corresponding location of the point and the distance from the point)

包括4天线准正交码的编码和解码程序，其中解码程序包括部分行的合并解码(Including 4 antenna quasi-orthogonal code encoding and decoding procedures, which include decoding part decoding the combined line)

Tschebyscheff滤波器设计，包括零极点分布，幅值相位的关系。(Tschebyscheff filter design, including the zero-pole distribution, the amplitude-phase relationship.)

ARDUINO I/O DEVELOPER

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)