Sepic

使用Matlab编写的一个dijkstra算法，非常的实际好用(Written using Matlab a dijkstra algorithm, a very practical easy to use)

图像认证中的Image Hashing技术，源码最新下载自美国名校The University of Texas at Austin的Brian L. Evans教授的实验室网站 (Matlab programs for image hashing downloaded from Professor Brian L. Evans in University of Texas at Austin in USA)

是一个显著性检测的典型算法，能够清楚的得到显著图(It is a typical algorithm for saliency detection, which can clearly get saliency map.)

battery model on simulink

这个是关于小波变换，对图像增强介绍的文章，共大家参考研究、使用。(This is the wavelet transform, image enhancement described in the article on the total of your reference and use.)

说明：  用matlab语言编写的ztc代码，实现将图像进行EZW编码解码和重构的过程。(Ztc written by matlab code to achieve the EZW image encoding and decoding and reconstruction。)

对正交幅度调制的发送和接受部分分别进行仿真分析。(Quadrature amplitude modulation for transmitting and receiving parts were simulated and analyzed.)

This demo nstrates 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. (This demo nstrates 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. )

NR潮流，主要应用于电力系统中。是一种基本的算法(NR powerflow, mainly used in power system.Is a basic algorithm)

含有噪声的多维非线性系统辨识！！！ (Noisy multi-dimensional non-linear system identification! ! !)