The PCI Local bus concept was developed to break the PC data I/O bottleneck and clearly opens the door to increasing system speed and expansion capabilities. The PCI Local bus moves high speed peripherals from the I/O bus and places them closer to the system’s processor bus, providing faster data transfers between the processor and peripherals. The PCI Local bus also addresses the industry’s need for a bus standard which is not directly dependent on the speed, size and type of system processor. It represents the first microprocessor independent bus offering performance more than adequate for the most demanding applications such as full-motion video. User Manual
標簽： bottleneck developed the concept
上傳時間： 2014-01-15
上傳用戶：努力努力再努力
The main purpose of this project is to add a new scheduling algorithm to GeekOS and to implement a simple synchronization primitive (semaphore). As you might have already noticed, GeekOS uses a simple priority based preemptive Round Robin algorithm. In this project, you will change this to a multilevel feedback scheduling. In addition, you will provide user programs with semaphores, a means to check the system s current time and a mechanism for passing command-line arguments
標簽： scheduling algorithm implement to
上傳時間： 2013-11-27
上傳用戶：Late_Li
Threads are essential to Java programming, but learning to use them effectively is a nontrivial task. This new edition of the classic Java Threads shows you how to take full advantage of Java s threading facilities and brings you up-to-date with the watershed changes in Java 2 Standard Edition version 5.0 (J2SE 5.0). It provides a thorough, step-by-step approach to threads programming.
標簽： effectively programming nontrivial essential
上傳時間： 2016-03-20
上傳用戶：hn891122
Basic hack v2.1 by xgx - http://www.ring0.donster.de/ Features: - Smooth Vector Aimbot - Full ESP ( Namen,Weapon,Distance,Visible,Far) - polymorph,peb hiding to prevent VAC detection
標簽： Features donster Aimbot Smooth
上傳時間： 2013-12-18
上傳用戶：agent
// // Histogram Sample // This sample shows how to use the Sample Grabber filter for video image processing. // Conceptual background: // A histogram is just a frequency count of every pixel value in the image. // There are various well-known mathematical operations that you can perform on an image // using histograms, to enhance the image, etc. // Histogram stretch (aka automatic gain control): // Stretches the image histogram to fill the entire range of values. This is a "point operation," // meaning each pixel is scaled to a new value, without examining the neighboring pixels. The // histogram stretch does not actually require you to calculate the full histogram. The scaling factor // is calculated from the minimum and maximum values in the image.
標簽： Sample Histogram Grabber sample
上傳時間： 2013-12-15
上傳用戶：ryb
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
ITU-T G.723.1 Speech Coder: Matlab implementation This package implements the speech coder and decoder. Full documentation is in the PDF file included with the package. The test folder has test programs for the coder and decoder (for Windows).
標簽： implementation implements package Speech
上傳時間： 2013-12-05
上傳用戶：qq521
* Explains process algebra and protocol specification using µ CRL, a language developed to combine process algebra and abstract data types * Text is supported throughout with examples and exercises * Full solutions are provided in an appendix, while exercise sheets, lab exercises, example specifications and lecturer slides are available on the author s website
標簽： specification developed Explains language
上傳時間： 2016-04-27
上傳用戶：笨小孩
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