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.
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.
** File name: target.h
** Last modified Date: 2004-09-17
** Last Version: 1.0
** Descriptions: header file of the specific codes for LPC2100 target boards
** Every project should include a copy of this file, user may modify it as ne
AC97 Sample Driver and Related Code Samples.
This directory contains a sample AC97 adapter driver and several related code samples.
These samples need to be compiled with the Windows .NET or Windows XP build environment but are binary compatible with older operating systems like Windows 2000. To build the samples, enter any Windows .NET or Windows XP build environment and run build –cZ from this directory. The AC97 sample driver also runs in Windows 98 Second Edition or Windows Me, but the property page DLL and control panel application do not. For more information, please refer to the readme.htm files in each subdirectory. The INF file in the driver directory installs all of the samples in the subdirectories. The header file in this directory defines the private property used by each of the samples.
The sample software includes, common library, peripheral APIs, and test modules
for the APIs. The common library include startup file, standard definition and
header files, processor specific setup module, generic interrupt related APIs,
timer routine, and scatter loading file. The peripheral directories include,
GPIO, PWM, Real-time clock, timer, SPI, I2C, Watchdog timer, UART, external
interrupt, etc.
加亮文本框
Lightbox v2.0 uses the Prototype Framework and Scriptaculous Effects Library. You will need to include these three Javascript files in your header.
