手機(jī)文件瀏覽器 Here are the sources to SMan v1.2c 1.2 is a major jump from v1.1. You will see this from the way the code has been restructured into multiple files. It also supports flip closed. However, to my chagrin, I made the mistake of assuming there will only be one flip closed view. :( That s changed in v1.3 :) 1.3 supports multiple flip closed views that can be easily added into SMan.
標(biāo)簽： from 1.2 the sources
上傳時(shí)間： 2015-03-31
上傳用戶：彭玖華
This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis function. It performs a global search in the joint space of the parameters and number of parameters, thereby surmounting the problem of local minima. It allows the user to choose among various model selection criteria, including AIC, BIC and MDL
標(biāo)簽： This reversible annealing the
上傳時(shí)間： 2015-07-19
上傳用戶：ma1301115706
Welcome to the ASTA 3 Help Tutorials. These are documented tutorials that included new user jump start, to file sends to server techniques with non-database servers showing how to use Providers and ServerMethods. A Current version of these tutorials can always be found on line
標(biāo)簽： documented Tutorials tutorials included
上傳時(shí)間： 2013-12-18
上傳用戶：gyq
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.
標(biāo)簽： sequential reversible algorithm nstrates
上傳時(shí)間： 2014-01-18
上傳用戶：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.
標(biāo)簽： reversible algorithm the nstrates
上傳時(shí)間： 2014-01-08
上傳用戶：cuibaigao
peg jump此游戲所用到的相關(guān)算法,這是java版本
上傳時(shí)間： 2013-12-24
上傳用戶：chenbhdt
peg jump 游戲，里面有文檔，有報(bào)告，還有代碼，基本實(shí)現(xiàn)這款游戲要求的所有功能
上傳時(shí)間： 2013-12-18
上傳用戶：皇族傳媒
設(shè)計(jì)一類peg jump問題的求解系統(tǒng)，初步掌握智能搜索算法中的盲目搜索和啟發(fā)式搜索這兩類基本方法，同時(shí)通過具體的問題體會(huì)搜索算法、數(shù)據(jù)結(jié)構(gòu)、程序設(shè)計(jì)等知識(shí)的綜合應(yīng)用。
上傳時(shí)間： 2016-12-23
上傳用戶：kbnswdifs
J-rio is a cool "jump and run " - game!
標(biāo)簽： J-rio cool game jump
上傳時(shí)間： 2013-12-14
上傳用戶：2525775
MATLAB Tutorial : For the beginners in MATLAB, this example code will provide a great jump start. The code has comprehensive comments to elaborate the functionality explicitly.
標(biāo)簽： MATLAB beginners Tutorial example
上傳時(shí)間： 2013-12-19
上傳用戶：lxm
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