In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets.
标签： Rauch-Tung-Striebel algorithm smoother which
上传时间： 2016-04-15
上传用户：zhenyushaw
This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
标签： sequential reversible algorithm nstrates
上传时间： 2014-01-18
上传用户：康郎
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.
标签： reversible algorithm the nstrates
上传时间： 2014-01-08
上传用户：cuibaigao
C++编写的针对CP5611 PCI卡的通讯程序Demo
上传时间： 2013-12-10
上传用户：kristycreasy
ST7540 Demo 下位机C程序，配合ST上微机软件，有需要得可以参考参考
上传时间： 2014-01-19
上传用户：royzhangsz
agg图形库在WINCE下的一个DEMO，演示了AGG如何在WINCE下用GDI画图。
上传时间： 2013-12-21
上传用户：mikesering
usb isp demo source code
上传时间： 2016-04-22
上传用户：LIKE
ucfs文件系统pc版的demo演示，提供ucfs在pc上移植的全套代码。
上传时间： 2016-04-23
上传用户：chenlong
MPEG2 Loopback Demo"实现1路D1格式视频DSP端采集、MPEG2编码、MPEG2解码和视频输出回放显示。 该演示程序共包括如下2个文件夹，每一个文件夹的内容介绍如下： 01. DSP out--该文件夹下包含本公司提供的DSP端应用程序，以.out文件形式给出。 02. Documents--该文件夹下包含演示程序使用说明文档。
上传时间： 2013-12-20
上传用户：13160677563
数据结构和算法一些demo 包括冒泡排序,选择排序，插入排序
上传时间： 2016-04-23
上传用户：ve3344
