-
多遠程二極管溫度傳感器-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.
標簽：
Considerat
Design
遠程
二極管
上傳時間：
2014-12-21
上傳用戶：ljd123456
-
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.
標簽：
CoolRunner-II
XAPP
CPLD
380
上傳時間：
2013-10-26
上傳用戶：kiklkook
-
．數據結構
假設有M個進程N類資源，則有如下數據結構：
MAX[M*N] M個進程對N類資源的最大需求量
AVAILABLE[N] 系統可用資源數
ALLOCATION[M*N] M個進程已經得到N類資源的資源量
NEED[M*N] M個進程還需要N類資源的資源量
2．銀行家算法
設進程I提出請求Request[N]，則銀行家算法按如下規則進行判斷。
(1)如果Request[N]<=NEED[I，N]，則轉(2)；否則，出錯。
(2)如果Request[N]<=AVAILABLE，則轉(3)；否則，出錯。
(3)系統試探分配資源，修改相關數據：
AVAILABLE=AVAILABLE-REQUEST
ALLOCATION=ALLOCATION+REQUEST
NEED=NEED-REQUEST
(4)系統執行安全性檢查，如安全，則分配成立；否則試探險性分配作廢，系統恢復原狀，進程等待。
3．安全性檢查
(1)設置兩個工作向量WORK=AVAILABLE；FINISH[M]=FALSE
(2)從進程集合中找到一個滿足下述條件的進程，
FINISH[i]=FALSE
NEED<=WORK
如找到，執行(3)；否則，執行(4)
(3)設進程獲得資源，可順利執行，直至完成，從而釋放資源。
WORK=WORK+ALLOCATION
FINISH=TRUE
GO TO 2
(4)如所有的進程Finish[M]=true，則表示安全；否則系統不安全。
標簽：
數據結構
進程
資源
上傳時間：
2014-01-05
上傳用戶：moshushi0009
-
數據結構
假設有M個進程N類資源，則有如下數據結構：
MAX[M*N] M個進程對N類資源的最大需求量
AVAILABLE[N] 系統可用資源數
ALLOCATION[M*N] M個進程已經得到N類資源的資源量
NEED[M*N] M個進程還需要N類資源的資源量
2．銀行家算法
設進程I提出請求Request[N]，則銀行家算法按如下規則進行判斷。
(1)如果Request[N]<=NEED[I，N]，則轉(2)；否則，出錯。
(2)如果Request[N]<=AVAILABLE，則轉(3)；否則，出錯。
(3)系統試探分配資源，修改相關數據：
AVAILABLE=AVAILABLE-REQUEST
ALLOCATION=ALLOCATION+REQUEST
NEED=NEED-REQUEST
(4)系統執行安全性檢查，如安全，則分配成立；否則試探險性分配作廢，系統恢復原狀，進程等待。
3．安全性檢查
(1)設置兩個工作向量WORK=AVAILABLE；FINISH[M]=FALSE
(2)從進程集合中找到一個滿足下述條件的進程，
FINISH[i]=FALSE
NEED<=WORK
如找到，執行(3)；否則，執行(4)
(3)設進程獲得資源，可順利執行，直至完成，從而釋放資源。
WORK=WORK+ALLOCATION
FINISH=TRUE
GO TO 2
(4)如所有的進程Finish[M]=true，則表示安全；否則系統不安全。
標簽：
數據結構
進程
資源
上傳時間：
2013-12-24
上傳用戶：alan-ee
-
* 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:
標簽：
USER_MSG_INTERCEPT
TeamInfo
client
search
上傳時間：
2016-01-22
上傳用戶：ynzfm
-
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.
標簽：
filtering
particle
Blackwellised
conditionall
上傳時間：
2014-12-05
上傳用戶：410805624
-
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 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.
標簽：
reversible
algorithm
the
nstrates
上傳時間：
2014-01-08
上傳用戶：cuibaigao
-
開源備份軟件源碼
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
標簽：
Automatic
Advanced
Maryland
Archiver
上傳時間：
2017-01-13
上傳用戶：xc216
-
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++的設計師和最早的實現者，也是《C++程序設計語言》、《帶標注的C++參考手冊》和《C++語言的設計與演化》的作者。他從丹麥Aarhus大學和英國牛津大學畢業，現在是AT&T大規模程序設計研究部的負責人，AT&T特別成員，AT&T貝爾實驗室特別成員，以及ACM特別成員。Stroustrup的研究興趣包括分布式系統、操作系統、模擬、設計和程序設計。他也是Addison·Wesley的C++In-Depth系列書籍的編輯。
標簽：
C++
上傳時間：
2022-02-01
上傳用戶：
