ITU-T Recommendation V.90 98年9月版本 A DIGITAL MODEM AND ANALOGUE MODEM PAIR FOR USE ON THE PUBLIC SWITCHED TELEPHONE NETwork (PSTN) AT DATA SIGNALLING RATES OF UP TO 56 000 bit/s DOWNSTREAM AND UP TO 33 600 bit/s UPSTREAM
標(biāo)簽： MODEM Recommendation ANALOGUE DIGITAL
上傳時(shí)間： 2014-01-17
上傳用戶：hn891122
一個(gè)很棒的網(wǎng)絡(luò)控制系統(tǒng)仿真軟件，truetime工具箱包括TrueTime Computer與Truetime NETwork 兩個(gè)接口模塊。計(jì)算機(jī)模塊具有靈活的實(shí)時(shí)內(nèi)核，A/D和D/A轉(zhuǎn)換器，網(wǎng)絡(luò)接口和外部通道。計(jì)算機(jī)模塊按照用戶定義的任務(wù)執(zhí)行，代碼采用Matlab或C++編寫。
標(biāo)簽： 網(wǎng)絡(luò)控制系統(tǒng) 仿真軟件
上傳時(shí)間： 2015-06-03
上傳用戶：ruixue198909
ITU-T Recommendation T.30(2005 09) SERIES T: TERMINALS FOR TELEMATIC SERVICES Procedures for document facsimile transmission in the general switched telephone NETwork
標(biāo)簽： Recommendation Procedures TERMINALS TELEMATIC
上傳時(shí)間： 2015-06-04
上傳用戶：shizhanincc
Beginning with an introduction to 802.11b in general, 802.11 Security gives you a broad basis in theory and practice of wireless security, dispelling some of the myths along the way. In doing so, they provide you with the technical grounding required to think about how the rest of the book applies to your specific needs and situations. If you are a NETwork, security, or systems engineer, or anyone interested in deploying 802.11b--based systems, you ll want this book beside you every step of the way.
標(biāo)簽： 802.11 introduction Beginning Security
上傳時(shí)間： 2013-12-04
上傳用戶：CHINA526
This program demonstrates some function approximation capabilities of a Radial Basis Function NETwork. The user supplies a set of training points which represent some "sample" points for some arbitrary curve. Next, the user specifies the number of equally spaced gaussian centers and the variance for the NETwork. Using the training samples, the weights multiplying each of the gaussian basis functions arecalculated using the pseudo-inverse (yielding the minimum least-squares solution). The resulting NETwork is then used to approximate the function between the given "sample" points.
標(biāo)簽： approximation demonstrates capabilities Function
上傳時(shí)間： 2014-01-01
上傳用戶：zjf3110
The Hopfield model is a distributed model of an associative memory. Neurons are pixels and can take the values of -1 (off) or +1 (on). The NETwork has stored a certain number of pixel patterns. During a retrieval phase, the NETwork is started with some initial configuration and the NETwork dynamics evolves towards the stored pattern which is closest to the initial configuration.
標(biāo)簽： model distributed associative Hopfield
上傳時(shí)間： 2015-06-17
上傳用戶：l254587896
本程序?yàn)閠cl程序，用于以ns2模擬ad hoc NETwork. 本程序?qū)嵶?0個(gè) nodes 在1000 * 1000公尺內(nèi)隨意移動的ad hoc NETwork.
上傳時(shí)間： 2014-01-27
上傳用戶：Thuan
This PNG Delphi version 1.56 documentation (this version is a major rewrite intended to replace the previous version, 1.2). Improvements in this new version includes: This new version allows the programmer to not use Delphi heavy units which will greatly reduce the size of the final executable. Read more about this feature here. Most, if not all, Portable NETwork Graphics features as CRC checking are now fully performed. Error on broken images are now better handled using new exception classes. The images may be saved using interlaced mode also. Transparency information won t be discarted after the image is loaded any more. Most of the images are decoded much faster now. The images will be better encoded using fresh new algorithms. IMPORTANT! Now transparency information is used to display images.
標(biāo)簽： version documentation intended rewrite
上傳時(shí)間： 2015-06-28
上傳用戶：qiao8960
The Netlab toolbox is designed to provide the central tools necessary for the simulation of theoretically well founded neural NETwork algorithms and related models for use in teaching, research and applications development. It contains many techniques which are not yet available in standard neural NETwork simulation packages
標(biāo)簽： simulation necessary the designed
上傳時(shí)間： 2013-12-11
上傳用戶：hj_18
This demo nstrates the use of the reversible jump MCMC simulated annealing for neural NETworks. This algorithm enables us to maximise the joint posterior distribution of the NETwork parameters and the number of basis function. It performs a global search in the joint space of the parameters and number of parameters, thereby surmounting the problem of local minima. It allows the user to choose among various model selection criteria, including AIC, BIC and MDL
標(biāo)簽： This reversible annealing the
上傳時(shí)間： 2015-07-19
上傳用戶：ma1301115706
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