FDM-in-Matlab

this mfile calculate y bus

通过非线性扩张观测器可实现被控对象的位置、速度和未知部分观测。在实际控制工程中，可采用本观测器实现无需速度测量的控制，并实现对未知不确定性和外加干扰补偿(Through the expansion of nonlinear observer can realize the location of the controlled object, speed and unknown part of the observation. Can be used in actual control engineering, the observer is to realize the control without speed measurement, and implement the unknown uncertainties and external disturbance compensation)

Calculate line residual in 3D

说明：  SCA算法实现，主要针对凸优化问题进行求解，可以在其他地方使用。(SCA algorithm, mainly for convex optimization problems, can be used in other places.)

本文主要是介绍了EKF与UKF的基本原理及其区别，主要适合讲课和作业运用(This paper introduces the basic principles of its distinction of EKF and UKF for lectures and operating use)

巴特沃夫高通滤波器通过高通滤波可用于检测奇异点。(Butterworth high-pass filter high-pass filter can be used to detect singular points.)

国外高校的关于图像区域生长的算法源码，编写的代码非常紧凑，算法执行效率高(Image region growing algorithm by abroad univertity and the algrorithm level is very high and efficient)

根据输入的概率进行香农编码，然后输出必要的参数和编码的结果。其中有嵌套程序。(Probability under the Importation of Shannon coding, and then output the necessary parameters and the coding results. Which have nested procedures.)

UNSW，GSOE9820 project management lecture notes

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.)