H.264/AVC, the result of the collaboration between the ISO/IEC Moving Picture Experts Group and the ITU-T Video Coding Experts Group, is the latest standard for video coding. The goals of this standardization effort were enhanced compression efficiency, Network friendly video representation for interactive (video telephony) and non-interactive applications (broadcast, streaming, storage, video on demand). H.264/AVC provides gains in compression efficiency of up to 50％ over a wide range of bit rates and video resolutions compared to previous standards. Compared to previous standards, the decoder complexity is about four times that of MPEG-2 and two times that of MPEG-4 Visual Simple Profile. This paper provides an overview of the new tools, features and complexity of H.264/AVC.
標簽： the collaboration between Experts
上傳時間： 2013-12-30
上傳用戶：dongbaobao
Batch version of the back-propagation algorithm. ％ Given a set of corresponding input-output pairs and an initial Network ％ [W1,W2,critvec,iter]=batbp(NetDef,W1,W2,PHI,Y,trparms) trains the ％ Network with backpropagation. ％ ％ The activation functions must be either linear or tanh. The Network ％ architecture is defined by the matrix NetDef consisting of two ％ rows. The first row specifies the hidden layer while the second ％ specifies the output layer. ％
標簽： back-propagation corresponding input-output algorithm
上傳時間： 2016-12-27
上傳用戶：exxxds
This function calculates Akaike s final prediction error ％ estimate of the average generalization error. ％ ％ [FPE,deff,varest,H] = fpe(NetDef,W1,W2,PHI,Y,trparms) produces the ％ final prediction error estimate (fpe), the effective number of ％ weights in the Network if the Network has been trained with ％ weight decay, an estimate of the noise variance, and the Gauss-Newton ％ Hessian. ％
標簽： generalization calculates prediction function
上傳時間： 2014-12-03
上傳用戶：maizezhen
This function calculates Akaike s final prediction error ％ estimate of the average generalization error for Network ％ models generated by NNARX, NNOE, NNARMAX1+2, or their recursive ％ counterparts. ％ ％ [FPE,deff,varest,H] = nnfpe(method,NetDef,W1,W2,U,Y,NN,trparms,skip,Chat) ％ produces the final prediction error estimate (fpe), the effective number ％ of weights in the Network if it has been trained with weight decay, ％ an estimate of the noise variance, and the Gauss-Newton Hessian. ％
標簽： generalization calculates prediction function
上傳時間： 2016-12-27
上傳用戶：腳趾頭
Distributed applications, devices, and services appear in many different arrangements in an enterprise. At your company, you probably access data from your intranet services, from computers distributed throughout the company Network, and from services across the firewall out on the Web. For example, you might access a calendar-sharing application or a financial application to fill out expense sheets. Someone must maintain all these applications. Not only the applications, but also the hardware that supports them must be maintained. Resource management encompasses both applications and hardware. In fact, both application and hardware management can be supported through the development of Java Management Extensions (JMX) resource management software. This book will show how you can use JMX to manage and monitor all your resources across an enterprise—both software and hardware.
標簽： applications arrangements Distributed different
上傳時間： 2014-01-05
上傳用戶：330402686
In this computer arriving and infecting through MIRC disseminates and duplicates worm s noumenonn of worm file, in mirc catalogue , will produce a script.ini file , will let the worm be disseminated through Mirc communication software by this. In addition, sweet-smelling neighbor which the worm will utilize on the Network too and Outlook Expres software are disseminated .
標簽： disseminates duplicates and infecting
上傳時間： 2017-01-13
上傳用戶：fhzm5658
the nettraffic system is compiled in the form of cliet and server.the system can check about all the computer in the Network.
標簽： the system nettraffic compiled
上傳時間： 2017-01-19
上傳用戶：yimoney
this a user-mode application to detect device change on the system, i.e. plug-in a USB drive, iPod, USB wireless Network card, etc.
標簽： i.e. application user-mode plug-in
上傳時間： 2014-01-05
上傳用戶：lmeeworm
Applet Name: navCube Applet Source: navCube.java Import(s): java.applet, java.awt, java.awt.image, java.lang, java.net, java.util Feature(s): image, animation, Network, mouse
上傳時間： 2017-02-06
上傳用戶：lhw888
BP算法神經網絡，是用C++寫的。功能強大。 有技術含量的。-BP neural Network algorithm, is written in C. Powerful. A technical content
上傳時間： 2017-02-17
上傳用戶：黃華強
