網絡安全編程之des加密算法實現有demo
上傳時間： 2014-01-26
上傳用戶：清風冷雨
SVM源碼，很有參考價值，很適和初學者學習，是matlab的
上傳時間： 2016-04-11
上傳用戶：xzt
游程編碼的一個演示程序, 用VC寫的Demo程序, 學習Run Length Coding時很好的參考資料.
上傳時間： 2016-04-11
上傳用戶：wanghui2438
SVM的matlab工具箱，可以實現支持向量基的分類和回歸問題
上傳時間： 2016-04-12
上傳用戶：lhw888
一個Java實現的支持向量機(含源碼),SVM算法比較復雜，不過這個程序看起來比較好懂。
上傳時間： 2013-12-26
上傳用戶：zhuoying119
ICC7AVR v7.13 Pro Loader 1.Install iccv7avr v7.13 demo 2.Copy IccAvrPro713.exe to ICCV7AVR bin folder, 3.Run IccAvrPro713.exe. 4.Enjoy!
標簽： 7.13 IccAvrPro ICCV7AVR iccv7avr
上傳時間： 2013-12-21
上傳用戶：小碼農lz
Keil的HTTP DEMO程序調試應用指南
上傳時間： 2014-01-27
上傳用戶：jhksyghr
In 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.
標簽： Rao-Blackwellised conditional filtering particle
上傳時間： 2013-12-14
上傳用戶：小儒尼尼奧
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.
標簽： Rauch-Tung-Striebel algorithm smoother which
上傳時間： 2016-04-15
上傳用戶：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.
標簽： sequential reversible algorithm nstrates
上傳時間： 2014-01-18
上傳用戶：康郎
