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隨機(jī)多址通信系統(tǒng)理論及仿真研究
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本書介紹了隨機(jī)多址通信系統(tǒng)廣泛應(yīng)用于物聯(lián)網(wǎng)、無(wú)線傳感器網(wǎng)絡(luò)、移動(dòng)互聯(lián)網(wǎng)絡(luò)、無(wú)線局域網(wǎng)、蜂窩通信網(wǎng)絡(luò)等通信技術(shù)的情況;對(duì)各類隨機(jī)多址通信系統(tǒng)進(jìn)行了建模分析,獲得了一系列的解析結(jié)果;介紹了各類系統(tǒng)的計(jì)算機(jī)仿真方法,給出了相關(guān)仿真結(jié)果。本書分為10章:第1章簡(jiǎn)要介紹后續(xù)部分將要進(jìn)行仿真的十九個(gè)協(xié)議,以及協(xié)議之間相應(yīng)的區(qū)別,讓讀者對(duì)隨機(jī)多址協(xié)議有一個(gè)整體的認(rèn)識(shí);第2章介紹本書仿真所使用的仿真軟件Matlab及仿真的具體流程;第3章詳細(xì)介紹ALOHA協(xié)議,以及其基于Matlab平臺(tái)的仿真具體方法;第4到第8章分別介紹非堅(jiān)持CSMA協(xié)議、1-堅(jiān)持CSMA協(xié)議、P-堅(jiān)持CSMA協(xié)議、P-檢測(cè)CSMA協(xié)議、二維概率CSMA協(xié)議和在其各自協(xié)議的基礎(chǔ)上改進(jìn)得來(lái)的兩個(gè)協(xié)議,以及協(xié)議基于Matlab平臺(tái)的具體仿真方法;第9章詳細(xì)介紹二叉樹沖突分解算法,以及其基于Matlab平臺(tái)的仿真具體方法;第10章對(duì)本書所涉及到的具體協(xié)議進(jìn)行比較,并做了一個(gè)簡(jiǎn)要的總結(jié)。本書可作為通信類專業(yè)的本科生和研究生的教材或參考書,也適合從事通信工程領(lǐng)域相關(guān)研究人員閱讀。

丁洪偉 柳虔林 趙一帆 周圣杰 楊志軍 ·電子通信 ·3.9萬(wàn)字

TensorFlow Machine Learning Cookbook
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Exploremachinelearningconceptsusingthelatestnumericalcomputinglibrary—TensorFlow—withthehelpofthiscomprehensivecookbookAboutThisBook?YourquickguidetoimplementingTensorFlowinyourday-to-daymachinelearningactivities?Learnadvancedtechniquesthatbringmoreaccuracyandspeedtomachinelearning?UpgradeyourknowledgetothesecondgenerationofmachinelearningwiththisguideonTensorFlowWhoThisBookIsForThisbookisidealfordatascientistswhoarefamiliarwithC++orPythonandperformmachinelearningactivitiesonaday-to-daybasis.Intermediateandadvancedmachinelearningimplementerswhoneedaquickguidetheycaneasilynavigatewillfindituseful.WhatYouWillLearn?BecomefamiliarwiththebasicsoftheTensorFlowmachinelearninglibrary?GettoknowLinearRegressiontechniqueswithTensorFlow?LearnSVMswithhands-onrecipes?Implementneuralnetworksandimprovepredictions?ApplyNLPandsentimentanalysistoyourdata?MasterCNNandRNNthroughpracticalrecipes?TakeTensorFlowintoproductionInDetailTensorFlowisanopensourcesoftwarelibraryforMachineIntelligence.TheindependentrecipesinthisbookwillteachyouhowtouseTensorFlowforcomplexdatacomputationsandwillletyoudigdeeperandgainmoreinsightsintoyourdatathaneverbefore.You’llworkthroughrecipesontrainingmodels,modelevaluation,sentimentanalysis,regressionanalysis,clusteringanalysis,artificialneuralnetworks,anddeeplearning–eachusingGoogle’smachinelearninglibraryTensorFlow.ThisguidestartswiththefundamentalsoftheTensorFlowlibrarywhichincludesvariables,matrices,andvariousdatasources.Movingahead,youwillgethands-onexperiencewithLinearRegressiontechniqueswithTensorFlow.Thenextchapterscoverimportanthigh-levelconceptssuchasneuralnetworks,CNN,RNN,andNLP.OnceyouarefamiliarandcomfortablewiththeTensorFlowecosystem,thelastchapterwillshowyouhowtotakeittoproduction.StyleandapproachThisbooktakesarecipe-basedapproachwhereeverytopicisexplicatedwiththehelpofareal-worldexample.

Nick McClure ·電子通信 ·7.7萬(wàn)字

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