ProbShrink

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. )

摩尔边界的源码在计算电磁学中有很大应用大家好好学习！！！(Moore border in the calculation of electromagnetic source in the study have significant application study hard everyone! ! !)

说明：  程序使用说明： 1、软件应用平台：Matlab6.5或更高； 2、打开方法： 将文件所在目录设为工作目录，然后打开wavlet.fig,在noise提示框下输入噪声强度，在0-0.1之间（不能为零）。 然后点process按钮，就会显示实验结果，包括原图像，加噪图像，去噪图像的对比以及当前的psnr值。 wavlet.m是程序文件。 程序内容写在在程序的注释里。 阈值的更改没有实现可视化，在源程序中可以改。(Procedure for use: 1, Software Platform: Matlab6.5 or higher 2, open the way: the file directory set the working directory, then open the wavlet.fig, the noise boxes, enter the noise level, in the 0-0.1 between (not zero). Then process the button, it will show the experimental results, including the original image, noise image denoising image contrast and the current psnr value. wavlet.m is the program file. Program content in the program notes written inside. Threshold changes are not visualized in the source program can be changed.)

说明：  运用粒子群算法优化支持向量机的参数，效果比较好(The use of particle swarm optimization algorithm for support vector machine parameters, the effect is better)

关于matlab优化工具箱使用的一些案例介绍。包含内容较为全面。可以作为入门使用。(Introduction matlab optimization toolbox to use some of the cases. Contains more comprehensive. Can be used as an entry.)

sprt code in matlab. sprt can isolate the change of variance in a signal.

Easy calculator dswafrefewfreqfr

Matrix Converter Commutation Strategies With and Without Explicit Input Voltage Sign Measurement

说明：  各种数码之间的相互转换，比如2进制转10进制(Base Conversion Algorithm)

IMPLEMENTATION OF LQG CONTROLLER