1_speed_control_pid

本程序是运用SVM来实现人脸识别算法，能直接运行且能进行二次开发(This procedure is to use SVM to implement face recognition algorithm that can run directly and can perform a secondary development)

PROGRAM hich is used to implement a back steeping and robust control with trajectory generation for planaire robot of two degree of freedem

窄带信号mvdr波束形成,这几天的学习结果(mvdr is written by me!)

数据拟合程序，可实现数据的三阶自定义函数的最小二乘拟合(Data fitting procedure, enabling third-order data, least squares fitting custom functions)

能量检测的ROC曲线，绝对有用。现存的有很多可能不满足你的要求，试试这个，如果好请给好评价，谢谢(ROC curve of energy detection is absolutely useful. There are many existing requirements may not meet you, try this, please give a good evaluation if good, thank you)

3d automation source running for curves manouvering

说明：  反距离插值，用于反距离插值，相对于其他算法，比较简单，效果也比较好(IDW,Inverse distance interpolation, which is used for inverse distance interpolation, is simpler and more effective than other algorithms.)

说明：  定时恢复仿真程序，可以解决定时不准确造成的定时错误(timing recovery simulation program can solve the timing of inaccurate timing error)

此算法先把伤病人员进行特殊对待，在计算出其他人的入院日期，表二的出院日期为 统计的期望值 运用是要改变 数据的初值 和u值（数据录入个数）；(This algorithm first special treat the sick and wounded, in the calculation of other people' s admission date, discharge date in Table II used for the statistical expectation is to change the initial data and u values ​ ​ (the number of data entry) )

可逆跳跃马尔科夫蒙特卡洛贝叶斯模型选择，主要用于神经网络(Reversible Jump MCMC Bayesian Model Selection This demo demonstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar-xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.)