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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
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D-S.Kim, Y.S.Lee, W.H.Kwon, and H.S.Park, "Maximum Allowable Delay Bounds in Networked Control Systems", Control Engineering Practice (Elsvier Science) (Simulation Example - Matlab Code), PP.1301-1313, Vol.11, Issue 11, December, 2003
標簽：
Allowable
Networked
Control
Maximum
上傳時間：
2016-04-10
上傳用戶：lifangyuan12
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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
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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
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The algorithms are coded in a way that makes it trivial to apply them to other problems. Several generic routines for resampling are provided. The derivation and details are presented in: Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas and Eric Wan. The Unscented Particle Filter. Technical report CUED/F-INFENG/TR 380, Cambridge University Department of Engineering, May 2000. After downloading the file, type "tar -xf upf_demos.tar" to uncompress it. This creates the directory webalgorithm containing the required m files. Go to this directory, load matlab5 and type "demo_MC" for the demo.
標簽：
algorithms
problems
Several
trivial
上傳時間：
2014-01-20
上傳用戶：royzhangsz
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This white paper describes a collection of standards, conventions, and guidelines for writing solid Java
code. They are based on sound, proven software engineering principles that lead to code that is easy to
understand, to maintain, and to enhance.
標簽：
conventions
collection
guidelines
describes
上傳時間：
2014-12-08
上傳用戶：hakim
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空間桁架的有限元分析源碼，是國外《intrduction to finite elements on engineering》中的。
標簽：
有限元分析
源碼
上傳時間：
2013-12-09
上傳用戶：Zxcvbnm
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Writing Robust Java Code
The AmbySoft Inc. Coding Standards for Java
v17.01d
Scott W. Ambler
Software Process Mentor
This Version: January 15, 2000
Copyright 1998-1999 AmbySoft Inc.Purpose of this White Paper
This white paper describes a collection of standards, conventio
code. They are based on sound, proven software engineering p
understand, to maintain, and to enhance. Furthermore, by foll
productivity as a Java developer should increase remarkably ¨C
write high-quality code right from the start you will have a much
development process. Finally, following a common set of codi
making teams of developers significantly more productive.
標簽：
W.
Java
Standards
AmbySoft
上傳時間：
2013-12-22
上傳用戶：mhp0114
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Aspect-Oriented Software Developement
Coverage includes
Using AOSD to streamline complex systems development without sacrificing flexibility or scalability
How AOSD builds on the object-oriented paradigmand how it s different
State-of-the-art best practices for the AOSD development process
Languages and foundations: separating concerns, filter technologies, improving modularity, integrating new features, and more
Using key AOSD tools, including AspectJ, Hyper/J, JMangler, and Java Aspect Components
Engineering aspect-oriented systems: UML, concern modeling and elaboration, dependency management, and aspect composition
Developing more secure applications with AOSD techniques
Applying aspect-oriented programming to database systems
Building dynamic aspect-oriented infrastructure
標簽：
Aspect-Oriented
Developement
streamline
Software
上傳時間：
2013-12-01
上傳用戶：jennyzai
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The widespread use of embedded systems mandates the development of industrial software design methods, i.e. computer-aided design and engineering of embedded applications using formal models (frameworks) and standardized prefabricated components, much in the same way as in other mature areas of engineering such as mechanical engineering and electronics. These guidelines have been used to develop Component-based Design of Software for Embedded Systems (COMDES). The paper gives an overview of the COMDES framework, followed by a presentation of a generic component types, such as function blocks, activities and function units. The execution of function units is discussed in the context of a newly developed execution model, i.e. timed-multitasking, which has been extended to distributed embedded systems.
標簽：
development
widespread
industrial
embedded
上傳時間：
2014-01-23
上傳用戶：z754970244
