TwoVariablesDistribution

ve-DYNA® 为用户提供了车辆动力学、车辆非线性行为的可配置仿真模型。用户根据自己的工程问题选择合适的车型（轿车，货车，拖车）和适当的版本（低级，标准，高级）就能实现不同的应用。用户基于模型就能开发自己的控制算法或者部件，然后通过离线仿真和硬件在回路仿真来进行检验和验证。只需要进行鼠标键盘的操作，就可以对种种的动力学问题进行分析，比如悬架动力学，车辆动力性或操纵稳定性。这样 就 能够减少昂贵而且费时甚至是危险的实车试验。可以在无人监控的情况下完成整个的测试、优化和系统验证 。本文为veDYNA软件的相关例程介绍。(ve-DYNA ® provides users with vehicle dynamics, nonlinear behavior can be configured vehicle simulation model. Users according to their engineering problems select the appropriate models (cars, trucks, trailers) and the appropriate version (low, standard, advanced) will be able to implement different applications. Users can develop their own model-based control algorithms, or parts, and then off-line simulation and hardware in the loop simulation to be tested and verified. Only for mouse and keyboard operation, it can analyze the various dynamics, such as suspension dynamics, vehicle dynamic performance or handling and stability. This can reduce the costly and time-consuming and even dangerous in real vehicle tests. No one can monitor the situation in the completion of the testing, optimization and system verification. This article related to software routines for the veDYNA introduction.)

一个基于DCT域的数字水印代码，里面有详细的注释说明。(This is a digital watermarking sourcecode based on DCT.Attached with detailed comments and explanation.)

利用Canny Filter找到图像的角点并且化出Box，可以用来进行图像配准(A Canny Cornner Detection programming with cornor box labelling. Good for image registration feature point matching.)

基于高斯线性的概率密度函数滤波估计，以此为蓝本有很多改进或类似的算法，比如CDKF-PHD等(Based on Gaussian probability density function of the linear filter estimation, there are a lot of improvements as a blueprint or similar algorithms, such CDKF-PHD, etc.)

program about ofdm for transmitter and receiver signal run using matlab

The matlab code for double pendulum

一个IEEE802.11b的实用例程，供大家参考。以5.5Mbps 为例。(5.5 Mbps CCK Simulation using specs from IEEE 802.11b, No guarantees and warantees!)

it is about binary phase shift keying

Space vector pulse width modulation

用MATLAB进行区间估计与线性回归分析的ppt课件，希望对大家有用(Carried out using MATLAB interval estimation and linear regression analysis ppt courseware, hope for all of us)