This a collection of MATLAB functions for extended Kalman filtering, unscented Kalman filtering, particle filtering, and miscellaneous other things. These utilities are designed for reuse and I have found them very useful in many projects. The code has been vectorised for speed and is stable and fast.
Debugging is a fascinating topic no matter what language or platform you re using. It s the only part of software development in which engineers kick, scream at, or even throw their computers. For a normally reticent, introverted group, this degree of emotion is extraordinary. Debugging is also the part of software development that s famous for causing you to pull all-nighter
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.
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.
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.
三星公司官方 GIVEIO.SYS源代碼下載。
In windows NT/2000/XP, any application can’t access the I/O such as the parallel port. So, GIVEIO.SYS enables
SJF.exe to access the parallel port without any memory fault. In windows 95/98, GIVEIO.SYS isn’t needed.
What I am trying to introduce here is a full fledged Java Instant messenger, which has all the features supplied by commercial messengers like Yahoo or MSN. Although it cannot compared to be in par with those messengers, it is an attempt by me to learn Advanced Java and JNI concepts. The challenges I faced here were often overcome by referring to numerous sites, which nearly zeroes in or completely solved the issues I faced at that point of time. It improved my learning curve and also believe would do the same to you too. Ofcourse, there are some bugs and glitches, which I hope you would excuse. Thanks to anyone who takes the pain to report them or even suggest better way of doing things to me.
