LPCARM之IAP应用举例及FLASH二次写入C++程序祥解。方便大家写程序参考.
上传时间： 2014-01-11
上传用户：watch100
使用USB接口实现AVR单片机ISP升级.
上传时间： 2013-12-26
上传用户：1079836864
自制的SyncMos的ISP下载源程序，厂商提供的下载代码和下载程序经常出错
上传时间： 2014-01-08
上传用户：linlin
ET++ is a portable and homogenous object-oriented class library integrating user interface building blocks, basic data structures, and high level application framework components. ET++ eases the building of highly interactive applications with consistent user interfaces following the direct manipulation principle. The ET++ class library is implemented in C++ and can be used on several operating systems and window system platforms. Since its initial conception the class library has been continuously redesigned and improved. It started with an architecture which was close to MacApp. During several iterations a new and unique architecture evolved. A byproduct of the ET++ project is a set of tools, which were designed to support the exploration of ET++ applications at run-time. 设计模式一书引用的主要参考例程，一个跨平台的应用框架，基于C++实现，是学习面向对象的经典源码.
标签： object-oriented integrating homogenous interface
上传时间： 2016-04-15
上传用户：tedo811
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.
标签： Rao-Blackwellised conditional filtering particle
上传时间： 2013-12-14
上传用户：小儒尼尼奥
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.
标签： Rauch-Tung-Striebel algorithm smoother which
上传时间： 2016-04-15
上传用户：zhenyushaw
NXP公司的arm系列芯片LPCXXXX的ISP烧写程序。
上传时间： 2016-04-15
上传用户：王者A
STM32F103 IAP程序，具体请查看www.elechome.com
上传时间： 2016-04-16
上传用户：水中浮云
ISP编程器驱动软件，提供了这个软件的全部资料及应用程序，是非常不错的软件
上传时间： 2014-12-06
上传用户：王楚楚
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.
标签： sequential reversible algorithm nstrates
上传时间： 2014-01-18
上传用户：康郎
