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  • 多远程二极管温度传感器 (Design Considerat

    多远程二极管温度传感器-Design Considerations for pc thermal management Multiple RDTS (remote diode temperature sensing) provides the most accurate method of sensing an IC’s junction temperature. It overcomes thermal gradient and placement issues encountered when trying to place external sensors. PCB component count decreases when using a device that provides multiple inputs.Better temperature sensing improves product performance and reliability. Disk drive data integrity suffers at elevated temperatures. IBM published an article stating that a 5°C rise in operating temperature causes a 15% increase in the drive’s failure rate. The overall performance of a system can be improved by providing a more accurate temperature measurement of the most critical devices allowing them to run just a few degrees hotter.The LM83 directly senses its own temperature and the temperature of three external PN junctions. One is dedicated to the CPU of choice, the other two go to other parts of your system that need thermal monitoring such as the disk drive or graphics chip. The SMBus-compatible LM83 supports SMBus timeout and logic levels. The LM83 has two interrupt outputs; one for user-programmable limits and WATCHDOG capability (INT), the other is a Critical Temperature Alarm output (T_CRIT_A) for system power supply shutdown.

    标签: Considerat Design 远程 二极管

    上传时间: 2014-12-21

    上传用户:ljd123456

  • XAPP380 -利用CoolRunner-II CPLD创建交叉点开关

      This application note provides a functional description of VHDL source code for a N x N DigitalCrosspoint Switch. The code is designed with eight inputs and eight outputs in order to targetthe 128-macrocell CoolRunner™-II CPLD device but can be easily expanded to target higherdensity devices. To obtain the VHDL source code described in this document, go to sectionVHDL Code, page 5 for instructions.

    标签: CoolRunner-II XAPP CPLD 380

    上传时间: 2013-10-26

    上传用户:kiklkook

  • .数据结构 假设有M个进程N类资源

    .数据结构 假设有M个进程N类资源,则有如下数据结构: MAX[M*N] M个进程对N类资源的最大需求量 AVAILABLE[N] 系统可用资源数 ALLOCATION[M*N] M个进程已经得到N类资源的资源量 NEED[M*N] M个进程还需要N类资源的资源量 2.银行家算法 设进程I提出请求Request[N],则银行家算法按如下规则进行判断。 (1)如果Request[N]<=NEED[I,N],则转(2);否则,出错。 (2)如果Request[N]<=AVAILABLE,则转(3);否则,出错。 (3)系统试探分配资源,修改相关数据: AVAILABLE=AVAILABLE-REQUEST ALLOCATION=ALLOCATION+REQUEST NEED=NEED-REQUEST (4)系统执行安全性检查,如安全,则分配成立;否则试探险性分配作废,系统恢复原状,进程等待。 3.安全性检查 (1)设置两个工作向量WORK=AVAILABLE;FINISH[M]=FALSE (2)从进程集合中找到一个满足下述条件的进程, FINISH[i]=FALSE NEED<=WORK 如找到,执行(3);否则,执行(4) (3)设进程获得资源,可顺利执行,直至完成,从而释放资源。 WORK=WORK+ALLOCATION FINISH=TRUE GO TO 2 (4)如所有的进程Finish[M]=true,则表示安全;否则系统不安全。

    标签: 数据结构 进程 资源

    上传时间: 2014-01-05

    上传用户:moshushi0009

  • 数据结构 假设有M个进程N类资源

    数据结构 假设有M个进程N类资源,则有如下数据结构: MAX[M*N] M个进程对N类资源的最大需求量 AVAILABLE[N] 系统可用资源数 ALLOCATION[M*N] M个进程已经得到N类资源的资源量 NEED[M*N] M个进程还需要N类资源的资源量 2.银行家算法 设进程I提出请求Request[N],则银行家算法按如下规则进行判断。 (1)如果Request[N]<=NEED[I,N],则转(2);否则,出错。 (2)如果Request[N]<=AVAILABLE,则转(3);否则,出错。 (3)系统试探分配资源,修改相关数据: AVAILABLE=AVAILABLE-REQUEST ALLOCATION=ALLOCATION+REQUEST NEED=NEED-REQUEST (4)系统执行安全性检查,如安全,则分配成立;否则试探险性分配作废,系统恢复原状,进程等待。 3.安全性检查 (1)设置两个工作向量WORK=AVAILABLE;FINISH[M]=FALSE (2)从进程集合中找到一个满足下述条件的进程, FINISH[i]=FALSE NEED<=WORK 如找到,执行(3);否则,执行(4) (3)设进程获得资源,可顺利执行,直至完成,从而释放资源。 WORK=WORK+ALLOCATION FINISH=TRUE GO TO 2 (4)如所有的进程Finish[M]=true,则表示安全;否则系统不安全。

    标签: 数据结构 进程 资源

    上传时间: 2013-12-24

    上传用户:alan-ee

  • * first open client.cpp and search for that USER_MSG_INTERCEPT(TeamInfo) over it u add this

    * first open client.cpp and search for that USER_MSG_INTERCEPT(TeamInfo) over it u add this Code: USER_MSG_INTERCEPT(Health) { BEGIN_READ(pbuf,iSize) me.iHealth = READ_BYTE() return USER_MSG_CALL(Health) } * then we search for int HookUserMsg (char *szMsgName, pfnUserMsgHook pfn) and add this Code: REDIRECT_MESSAGE( Health ) *k now we have the health registered and can read it out i stop this hear know cuz i must thanks panzer and w00t.nl that they helped me with it first time! *ok now we go to int HUD_Redraw (float x, int y) and packing this draw code in it Code:

    标签: USER_MSG_INTERCEPT TeamInfo client search

    上传时间: 2016-01-22

    上传用户:ynzfm

  • The software implements particle filtering and Rao Blackwellised particle filtering for conditionall

    The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generic and suitable for any application. For details, please refer to Rao-Blackwellised Particle Filtering for Fault Diagnosis and On Sequential Simulation-Based Methods for Bayesian Filtering After downloading the file, type "tar -xf demo_rbpf_gauss.tar" to uncompress it. This creates the directory webalgorithm containing the required m files. Go to this directory, load matlab and run the demo.

    标签: filtering particle Blackwellised conditionall

    上传时间: 2014-12-05

    上传用户:410805624

  • In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve r

    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

  • This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hier

    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.

    标签: reversible algorithm the nstrates

    上传时间: 2014-01-08

    上传用户:cuibaigao

  • 开源备份软件源码 AMANDA, the Advanced Maryland Automatic Network Disk Archiver, is a backup system that a

    开源备份软件源码 AMANDA, the Advanced Maryland Automatic Network Disk Archiver, is a backup system that allows the administrator to set up a single master backup server to back up multiple hosts over network to tape drives/changers or disks or optical media. Amanda uses native dump and/or GNU tar facilities and can back up a large number of workstations running multiple versions of Unix. Amanda uses Samba, Cygwin or a native Windows client to back up Microsoft Windows desktops and servers

    标签: Automatic Advanced Maryland Archiver

    上传时间: 2017-01-13

    上传用户:xc216

  • The C++ Programming Language第四版

     Extensively rewritten to present the C++11 language, standard library, and key design techniques as an integrated whole, Stroustrup thoroughly addresses changes that make C++11 feel like a whole new language, offering definitive guidance for leveraging its improvements in performance, reliability, and clarity. C++ programmers around the world recognize Bjarne Stoustrup as the go-to expert for the absolutely authoritative and exceptionally useful information they need to write outstanding C++ programs. Now, as C++11 compilers arrive and development organizations migrate to the new standard, they know exactly where to turn once more: Stoustrup's C++ Programming Language, Fourth Edition.Bjarne Stroustrup是C++的设计师和最早的实现者,也是《C++程序设计语言》、《带标注的C++参考手册》和《C++语言的设计与演化》的作者。他从丹麦Aarhus大学和英国牛津大学毕业,现在是AT&T大规模程序设计研究部的负责人,AT&T特别成员,AT&T贝尔实验室特别成员,以及ACM特别成员。Stroustrup的研究兴趣包括分布式系统、操作系统、模拟、设计和程序设计。他也是Addison·Wesley的C++In-Depth系列书籍的编辑。

    标签: C++

    上传时间: 2022-02-01

    上传用户:jimmy950583