JAVA得到网卡物理地址(windows和Linux) ,当时觉得挺好,后来正好项目里有需要,就用了它,但好像有点问题.因为它是采用固定字符串搜索(if (line.indexOf("Physical Address") != -1) )获得MAC 地址的,后来在应用时出了问题,因为没有"Physical Address"这一项.后来在外网在查查了一下,后来发现老外有写一个这样的类,可能那样的方式更加可靠一点.算是做个标记
标签： Physical windows indexOf Linux
上传时间： 2016-01-24
上传用户：脚趾头
TOOL (Tiny Object Oriented Language) is an easily-embedded, object-oriented, C++-like-language interpreter. The language, and indeed a significant part of the core of the TOOL engine, is based on the BOB project, a work that was originally developed by David Betz covered in previously published issues of Dr. Dobb s Journal.
标签： easily-embedded object-oriented like-language Language
上传时间： 2016-01-30
上传用户：ainimao
The line echo canceller (LEC) is designed to provide the maximum attainable transparent voice quality for de-echoing of a PSTN or POTS connection in voice-over-LAN systems with internal delays, or on a codec end of a telecom switch,基于TI 54X/55X平台
标签： transparent attainable canceller designed
上传时间： 2014-01-17
上传用户：qoovoop
An object-oriented C++ implementation of Davidson method for finding a few selected extreme eigenpairs of a large, sparse, real, symmetric matrix
标签： object-oriented implementation Davidson eigenpai
上传时间： 2014-01-09
上传用户：TRIFCT
It is siemens plc program,it is our work-shop of an assembly line turning out cars program.
标签： program work-shop assembly siemens
上传时间： 2016-03-15
上传用户：yph853211
dsPIC DSC Line Echo Cancellation Library
标签： Cancellation Library dsPIC Line
上传时间： 2013-12-31
上传用户：王小奇
samples for pipe line source code
上传时间： 2013-12-12
上传用户：comua
候捷 inside object Oriented C
上传时间： 2016-04-02
上传用户：ardager
Demonstrates how to open a line and get general information
标签： Demonstrates information general open
上传时间： 2016-04-04
上传用户：playboys0
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.
标签： demonstrates sequential Selection Bayesian
上传时间： 2016-04-07
上传用户：lindor
