Transportation-Problem

说明：  通信系统离散信道仿真，散射、离散多径信道衰落模型mfiles(Communication system discrete channel simulation, scattering/discrete multipath fading channel matlab mfiles)

本论文主要说明数字中频GPS信号的MATLAB仿真，有较详细的仿真图(This thesis describes the MATLAB simulation of the digital IF GPS signals, a more detailed simulation in Figure)

通过现实数据集对混合蛙跳算法SFLA聚类性能进行评测，得到图示说明算法性能。(Real data set by clustering performance evaluation of SFLA to get illustrates algorithm performance.)

ECEF2ECI and ECI2ECEF坐标转换

平差辅助函数，用于平差过程中需要使用的函数模型(Adjustment helper function for function model adjustment process requires the use of)

在matlab中，采用模糊神经网络对监控水资源(In matlab using fuzzy neural network monitoring water)

有关向量2Z变换的matlab源码，有兴趣的同学可以看一看(2Z transformation of the vector matlab source, interested students can take a look at the)

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)

PCA based program for face recognition / classification

feature map for histogram intersection, map the data from hist intersection kernel to linear kernel(feature map for histogram intersection)