On-Line MCMC Bayesian Model Selection This demo demonstrates 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： demonstrates sequential Selection Bayesian
上传时间： 2016-04-07
上传用户：lindor
Atheros无线芯片AR-6000系列wince 6驱动源代码(这东西我也没用过别问我,我是搜别的wince资源搜到的) AR6K SDIO support. Requires firmware 1.1 on SD13 cards. readme: Atheros Communications AR6001 WLAN Driver for SDIO installation Read Me March 26,2007 (based on k14 fw1.1) Windows CE Embedded CE 6.0 driver installation. 1. Unzip the installation file onto your system (called installation directory below) 2. Create an OS design or open an existing OS design in Platform Builder 6.0. a. The OS must support the SD bus driver and have an SD Host Controller driver (add these from Catalog Items). b. Run image size should be set to allow greater than 32MB. 3. a. From the Project menu select Add Existing Subproject... b. select AR6K_DRV.pbxml c. select open This should create a subproject within your OS Design project for the AR6K_DRV driver. 4. Build the solution. 转自Tony嵌入式,原文地址：http://www.cevx.com/bbs/dispbbs.asp?boardID=4&ID=11762&page=1
标签： wince Requires firmware Atheros
上传时间： 2014-11-11
上传用户：bibirnovis
MX21 CSI driver user mode library * * This program is free software you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation either version 2 of the License, or * (at your option) any later version.
标签： redistribute software library program
上传时间： 2016-04-10
上传用户：himbly
* This file is part of DigitalWatch, a free DTV watching and recording * program for the VisionPlus DVB-T. * * DigitalWatch is free software you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation either version 2 of the License, or * (at your option) any later version.
标签： DigitalWatch VisionPlu recording watching
上传时间： 2014-08-27
上传用户：水口鸿胜电器
* This file is part of DigitalWatch, a free DTV watching and recording * program for the VisionPlus DVB-T. * * DigitalWatch is free software you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation either version 2 of the License, or * (at your option) any later version.
标签： DigitalWatch VisionPlu recording watching
上传时间： 2013-12-18
上传用户：dongbaobao
GTK SWF Player. GNOME Applications and a mozilla plugin. Other things included is a library for reading swf files, swf2txt convert swf to text files.
标签： Applications included mozilla library
上传时间： 2013-12-23
上传用户：TF2015
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
The BeeStack Application Development Guide describes how to develop an application for BeeStack, including discussions on major considerations for commercial applications. This document is intended for software developers who write applications for BeeStack-based products using Freescale development tools. It is assumed the reader is a programmer with at least rudimentary skills in the C programming language and that the reader is already familiar with the edit/compile/debug process.
标签： BeeStack Application Development application
上传时间： 2016-04-17
上传用户：lijianyu172
北京大学ACM比赛题目 In 1742, Christian Goldbach, a German amateur mathematician, sent a letter to Leonhard Euler in which he made the following conjecture: Every even number greater than 4 can be written as the sum of two odd prime numbers. For example: 8 = 3 + 5. Both 3 and 5 are odd prime numbers. 20 = 3 + 17 = 7 + 13. 42 = 5 + 37 = 11 + 31 = 13 + 29 = 19 + 23. Today it is still unproven whether the conjecture is right. (Oh wait, I have the proof of course, but it is too long to write it on the margin of this page.) Anyway, your task is now to verify Goldbach s conjecture for all even numbers less than a million.
标签： mathematician Christian Goldbach Leonhard
上传时间： 2016-04-22
上传用户：wangchong
