測(cè)試stc89C58單片機(jī) 測(cè)試stc89C58單片機(jī) 測(cè)試stc89C58單片機(jī)DEMO 程序
上傳時(shí)間： 2014-01-06
上傳用戶：hj_18
BOOSTING DEMO, A VERY USEFUL DEMO FOR ADABOOST
標(biāo)簽： DEMO BOOSTING ADABOOST USEFUL
上傳時(shí)間： 2013-12-08
上傳用戶：chenxichenyue
AT91SAM7S64 demo source code
標(biāo)簽： source SAM7 demo code
上傳時(shí)間： 2013-12-14
上傳用戶：tonyshao
SUNPLUS(凌陽(yáng)）GPC1XX demo程序，6502指令
標(biāo)簽： SUNPLUS GPC1XX demo 凌陽(yáng)
上傳時(shí)間： 2013-12-23
上傳用戶：lmeeworm
n this demo, we show how to use Rao-Blackwellised particle filtering to exploit the conditional independence structure of a simple DBN. The derivation and details are presented in A Simple Tutorial on Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. This detailed discussion of the ABC network should complement the UAI2000 paper by Arnaud Doucet, Nando de Freitas, Kevin Murphy and Stuart Russell. After downloading the file, type "tar -xf demorbpfdbn.tar" to uncompress it. This creates the directory webalgorithm containing the required m files. Go to this directory, load matlab5 and type "dbnrbpf" for the demo.
標(biāo)簽： Rao-Blackwellised conditional filtering particle
上傳時(shí)間： 2013-12-17
上傳用戶：zhaiyanzhong
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.
標(biāo)簽： demonstrates sequential Selection Bayesian
上傳時(shí)間： 2016-04-07
上傳用戶：lindor
介紹水晶報(bào)表使用的一個(gè)文檔,其中有在WINDOWS中使用水晶報(bào)表的DEMO
標(biāo)簽： WINDOWS DEMO 報(bào)表 文檔
上傳時(shí)間： 2013-11-29
上傳用戶：363186
crc算法c＋＋實(shí)現(xiàn)源代碼老外寫的 附demo
上傳時(shí)間： 2016-04-11
上傳用戶：xauthu
網(wǎng)絡(luò)安全編程之des加密算法實(shí)現(xiàn)有demo
標(biāo)簽： demo des 網(wǎng)絡(luò)安全 編程
上傳時(shí)間： 2014-01-26
上傳用戶：清風(fēng)冷雨
游程編碼的一個(gè)演示程序, 用VC寫的Demo程序, 學(xué)習(xí)Run Length Coding時(shí)很好的參考資料.
標(biāo)簽： Coding Length Demo Run
上傳時(shí)間： 2016-04-11
上傳用戶：wanghui2438
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