Lohman-holograms

这是一个关于二维的FDTD的源代码，主要模仿电磁波传播的传播，对于做天线，雷达的朋友有帮助(This is one of the two dimensional FDTD source code, mainly to imitate the propagation of electromagnetic wave propagation, for antenna, radar has to help a friend)

用于实现车道线识别探测的matlab程序，可达到良好的识别率(Lane Recognition for achieving detection matlab program, can achieve good recognition rate)

power system economics

最优化计算中一维无约束极值问题，适合初学者入门学习！(Optimize the calculation of one-dimensional unconstrained extremum problem, suitable for beginner to learn!)

matlab simulink倒立摆建模，适用于模糊控制算法(Inverted Pendulum Model Using Simulink)

A very simple Gaussian elimination code in matlab

使用EKF和粒子滤波在简单的平台上实现定位，是本人在华盛顿大学机器人课程作业的基础上编写完成的，可以作为滤波和移动机器人定位的基础教程使用。 Author：Wilford Wang PS. 可以先下载本人之前上传的Project-1.rar(华盛顿大学的课题作业)，自行编写，再与我写的程序做比较，可以达到比较好的学习效果。(Using the EKF and particle filter in a simple platform for location, is my course work at the University of Washington, based on the robot to complete the writing can be used as filtering and mobile robot localization based tutorial. Author: Wilford Wang PS. Before I can upload to download the Project-1.rar (University of Washington project work), write your own, and I wrote the program and then compare, you can achieve better learning results.)

非线性规划中的最陡下降法、BFGS方法和共轭梯度法matlab源程序（3－拟牛顿BFGS方法）.m(Non-linear programming in the steepest descent method, BFGS and conjugate gradient method matlab source code (3- Quasi-Newton BFGS method). M)

这篇文章是盲信号处理，因为是英文文章，所以大家看内容就好了。(Principal component analysis (PCA) is a mainstay of modern data analysis- a black box that is widely used but poorly understood. The goal of this paper is to dispel the magic behind this black box. This tutorial focuses on building a solid intuition for how and why principal component analysis works furthermore, it crystallizes this knowledge by deriving from simple intuitions, the mathematics behind PCA . This tutorial does not shy away from explaining the ideas informally, nor does it shy away from the mathematics. The hope is that by addressing both aspects, readers of all levels will be able to gain a better understanding of PCA as well as the when, the how and the why of applying this technique.)

mathlab code for tdoa demo