pml

时域有限差分方法在一维格子中计算麦克斯韦旋度方程(the finite-difference time-domain solution of Maxwell s curl equations over a one-dimensional space lattice comprised of uniform grid cells)

超宽带程序示范程序\M-PSK4psk.rar(Ultra-wideband Program Files demonstration program M-PSK 4psk.rar)

利用正弦信号作为发射信号，分别在AWGN和瑞利信道中，计算CR中的检测概率和虚警概率，并绘图。(Sinusoidal signal as transmitted signal, respectively, in AWGN and Rayleigh channel, calculate the probability of detection and false alarm probability of CR and drawing.)

in this package are the programs needed to solve any system of nonlinear equations

说明：  高光谱遥感图像压缩的lbg算法，十分经典(Hyperspectral remote sensing image compression lbg algorithm, very classic)

matlab 经典例程里的各种绘图函数，对迅速掌握matlab相关绘图工具很有帮助(the Matlab classic routines in a variety of drawing functions, quickly grasp the matlab drawing tools helpful)

判断半正定矩阵与正定矩阵间的一种新的准则，gky方法是判定系统是否稳定的一种很有效的方法，里面有源代码和相应文档(Judge half positive definite matrix and the positive definite matrix, a new criterion between gky method is to determine whether the system stability of a kind of very effective method, there are source code and documentation accordingly)

FFT_ by Matlab_Sound1

matlab英文教材：matlab在高等数学与应用力学上的应用(English teaching materials matlab: matlab mathematics and applied mechanics in the application)

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)