Useofmatlabtutorialofdigitalimageprocessing

matlab高级讲义，希望对初学者有用。里面有根讲义配套的程序代码(matlab advanced lectures, I hope it will be useful for beginners)

load flow study using gauss siedel method

30个案例分析 神经网络的30个案例分析一书地29个案例(30 case analysis)

纯相位空间光调制器相息图，产生相位信息，反射式空间光调制器(Pure phase spatial light modulator Kinoform)

MATLAB是美国MathWorks公司出品的商业数学软件，用于算法开发、数据可视化、数据分析以及数值计算的高级技术计算语言和交互式环境，主要包括MATLAB和Simulink两大部分。(MATLAB is a commercial mathematical software produced by MathWorks company, senior technical computing for algorithm development, data visualization, data analysis and numerical computing language and interactive environment, including MATLAB and Simulink two parts.)

beamformer code using c lang

说明：  潮流计算节点电压功率，潮流网损 输入格式 节点总数 PQ节点数 PV节点数 支路数 变压器支路数 （数据） 节点 P Q （PQ节点） ... ... .... 节点 P V （PV节点） ... ... .... 节点 V o（相角°） （平衡节点） 节点一 节点二 电阻 电抗 半电纳 (普通支路) ... ... .... ... ... 节点一 节点二 电阻 电抗 变比标幺值 （变压器支路，阻抗归 ... ... .... ... ... 算到节点一一侧）(Power flow calculation,including node voltage power and power flow network loss.)

用Lax-Friedrichs及Courant-Isaacson-Rees格式求解一阶双曲型方程。(With the Lax-Friedrichs and the Courant-Isaacson-Rees format for solving first order hyperbolic equation.)

说明：  ecg信号读取与二进制到十进制转换，为处理做准备(read ecg signal with the binary to decimal conversion, in preparation for the treatment)

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)