CForms, by Lars Berntzon (Stockholm, Sweden), is a tool for building interactive forms-driven applications. CForms applications can run on nany type of library supported by the "curses" library. CForms uses a language-based design to define forms. An application may contain C source modules, field pictures, field definitions, literals, and events. CForms applications must be compiled with the CFC compiler and linked with the CFL linker.CForms runs on most Unix SYSV compatible platforms including SunOS, Dell-SVR4, and Diab SYSV.3. It requires a curses library and yacc or GNU Bison. CForms version 2.1 is now available as volume #402 in the CUG Library.
標簽： forms-driven interactive Stockholm Berntzon
上傳時間： 2013-12-20
上傳用戶：himbly
This program is free software you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation either version 2 of the License, or * (at your option) any later version.
標簽： redistribute the software program
上傳時間： 2016-04-10
上傳用戶：2467478207
MX21 CSI driver user mode library * * This program is free software you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation either version 2 of the License, or * (at your option) any later version.
標簽： redistribute software library program
上傳時間： 2016-04-10
上傳用戶：himbly
MX21 IM8012 driver This program is free software you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation either version 2 of the License, or (at your option) any later version.
標簽： redistribute software program driver
上傳時間： 2013-12-19
上傳用戶：qazxsw
Sofia-SIP is an open-source SIP User-Agent library, compliant with the IETF RFC3261 specification. It can be used as a building block for SIP client software for uses such as VoIP, IM, and many other real-time and person-to-person communication services. The primary target platform for Sofia-SIP is GNU/Linux.
標簽： specification open-source User-Agent Sofia-SIP
上傳時間： 2016-04-10
上傳用戶：watch100
構建嵌入式Linux系統的詳細文檔，系統啟動bootloader的編寫，GNU交叉工具鏈的構建，u-boot的移植,linux2.6內核的移植,應用程序的移植 NAND flash驅動的編寫與移植
上傳時間： 2014-01-19
上傳用戶：bibirnovis
* This file is part of DigitalWatch, a free DTV watching and recording * program for the VisionPlus DVB-T. * * DigitalWatch is free software you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation either version 2 of the License, or * (at your option) any later version.
標簽： DigitalWatch VisionPlu recording watching
上傳時間： 2014-08-27
上傳用戶：水口鴻勝電器
* This file is part of DigitalWatch, a free DTV watching and recording * program for the VisionPlus DVB-T. * * DigitalWatch is free software you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation either version 2 of the License, or * (at your option) any later version.
標簽： DigitalWatch VisionPlu recording watching
上傳時間： 2013-12-18
上傳用戶：dongbaobao
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
