// Hint: These classes are intended to be used as base classes. Do not // simply add your code to these files - instead create a new class // derived from one of CSizingControlBarXX classes and put there what // you need. See CMyBar classes in the demo projects for examples.
標簽： classes intended simply These
上傳時間： 2016-04-07
上傳用戶：thinode
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.
標簽： demonstrates sequential Selection Bayesian
上傳時間： 2016-04-07
上傳用戶：lindor
Hibernate: A Developer s Notebook shows you how to use Hibernate to automate persistence: you write natural Java objects and some simple configuration files, and Hibernate automates all the interaction between your objects and the database. You don t even need to know the database is there, and you can change from one database to another simply by changing a few statements in a configuration file. If you ve needed to add a database backend to your application, don t put it off. It s much more fun than it used to be, and Hibernate: A Developer s Notebook shows you why.
標簽： Hibernate persistence Developer you
上傳時間： 2016-04-07
上傳用戶：123啊
Here we are at the crossroads once again Youre telling me youre so confused You cant make up your mind Is this meant to be Youre asking me Trademark But only love can say - try again or walk away But I believe for you and me The sun will shine one day So Ill just play my part And pray you ll have a change of heart But I cant make you see it through Thats something only love can do Face to face and a thousand miles apart Ive tried my best to make you see Theres hope beyond the pain If we give enough if we learn to trust [Chorus] I know if I could find the words To touch you deep inside Youd give our dream just one more chance Dont let this be our good-bye
標簽： crossroads confused telling again
上傳時間： 2016-04-12
上傳用戶：changeboy
Without this, the debugger spontaneously fails! 1 - Install mdk315b 2 - Replace the files: \Keil\ARM\BIN\ARM.DLL with one from mdk305a\Keil\ARM\BIN\ARM.DLL \Keil\ARM\BIN31\ARM.DLL with one from mdk305a\Keil\ARM\BIN30\ARM.DLL \Keil\UV3\UV3.DLL with one from mdk305a\Keil\UV3\UV3.DLL (*) 3 - Use KeyGen (Ver3p4 works) Select ARM, With computer ID code , External CID code and RealView MDK (or RealView RL) Note: Must replace DLLs before entry of serial (*) - May not be necessary (???)
標簽： spontaneously the debugger Without
上傳時間： 2016-04-13
上傳用戶：小寶愛考拉
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
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.
標簽： reversible algorithm the nstrates
上傳時間： 2014-01-08
上傳用戶：cuibaigao
This Two-Category Classifier Using Discriminant Functions to separeate two classes. The Classifier is designed on classes which has two feature vectors and other case it has one feature vector.
標簽： Classifier Discriminant Two-Category Functions
上傳時間： 2016-04-23
上傳用戶：2525775
神經網絡工具箱，包含SVM和NPA、"one-against-all" 、"one-against-one" 算法，有大量的例子。
上傳時間： 2016-04-23
上傳用戶：xhz1993
A technical trading system comprises a set of trading rules that can be used to generate trading signals. In general, a simple trading system has one or two parameters that determine the timing of trading signals. Each rule contained in a trading system is the results of parameterizations. (Source: The Profitability of Technical Analysis: A Review by Cheol-Ho Park and Scott H. Irwin)
標簽： trading technical comprises generate
上傳時間： 2013-12-25
上傳用戶：tianyi223
