【正版新书】信息理论基础英文版
【正版书籍 可开发票】
￥ 12.5 4.3折 ￥ 29 全新
库存2件
河北保定
认证卖家担保交易快速发货售后保障
作者陈杰,孙兵,于泽,周荫清
出版社北京航空航天大学出版社
ISBN9787512419728
出版时间2016-02
装帧其他
开本其他
定价29元
货号L9787512419728
上书时间2024-08-28
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内容简介:
Thisbooksystematicallyintroducedthefundamentalsofinformationtheory,focusingonthebasicmodelofcommunicationsystems．Itconsistsof11Chapters,includingtwoparts,namely,basicconceptionsofinforＧmationtheoryandrelatedapplicationsofinformationtheory．Thefirstpartcontainsstatisticalmeasureofinformation,discretesource,losslesssourcecodinganddatacompression,discretechannelanditscapacity,channelcoding,whilethesecondpartincludesratedistortion,continuoussource,continuouschannelanditscapacity,maximumentropyandspectrumestimationaswellascomputersimulationexperimentsrelevanttoinformationtheory． Thisbooksummarizedtheexperienceoftheauthorsonteachinginformationcoursein EnglishandChinese,togetherwiththeirunderstandingsfromyearsscientificresearchpractice．Itcanbeusedasteachingmaterialoninformationtheorycourseforbothinternationalundergraduateandgraduatestudents．
目录:
Chapter1 Introduction ………………………………………………………………………… 11．1 Conceptofinformation ………………………………………………………………… 11．2 Historyofinformationtheory ………………………………………………………… 21．3 Information,messagesandsignals …………………………………………………… 31．4 Communicationsystem model ………………………………………………………… 31．5 Informationtheoryapplications ……………………………………………………… 41．5．1 Electricalengineering(communicationtheory)………………………………… 41．5．2 Computerscience(algorithmiccomplexity) …………………………………… 5Exercises ……………………………………………………………………………………… 5Chapter2 StatisticalMeasureofInformation ………………………………………………… 62．1 Informationofrandomevents ………………………………………………………… 62．1．1 SelfＧinformation …………………………………………………………………… 62．1．2 ConditionalselfＧinformation ……………………………………………………… 62．1．3 Mutualinformationofevents …………………………………………………… 72．2 Informationofdiscreterandomvariables …………………………………………… 82．2．1 Entropyofdiscreterandomvariables …………………………………………… 82．2．2 Jointentropy……………………………………………………………………… 112．2．3 Conditionalentropy ……………………………………………………………… 112．2．4 Mutualinformationofdiscreterandomvariables …………………………… 112．3 Relationshipbetweenentropyandmutualinformation …………………………… 112．4 Mutualinformationandentropyofcontinuousrandomvariables………………… 122．4．1 Mutualinformationofcontinuousrandomvariables ………………………… 122．4．2 Entropyofcontinuousrandomvariables ……………………………………… 13Exercises ……………………………………………………………………………………… 14Chapter3 DiscreteSourceandItsEntropyRate …………………………………………… 153．1 Mathematicalmodelofsource ……………………………………………………… 153．1．1 Discretesourceandcontinuoussource ………………………………………… 163．1．2 Simplediscretesourceanditsextension ……………………………………… 173．1．3 Memorylesssourceandsourcewithmemory ………………………………… 183．2 Discretememorylesssource ………………………………………………………… 183．2．1 Definition ………………………………………………………………………… 183．2．2 Extensionofdiscretesource …………………………………………………… 193．3 Discretestationarysource …………………………………………………………… 203．3．1 Definition ………………………………………………………………………… 203．3．2 Entropyrateofdiscretestationarysource …………………………………… 213．4 DiscreteMarkovsource ……………………………………………………………… 243．4．1 Markovchain …………………………………………………………………… 243．4．2 Transitionprobability …………………………………………………………… 253．4．3 Markovsourceanditsentropyrate …………………………………………… 28Exercises ……………………………………………………………………………………… 31Chapter4 LosslessSourceCodingandDataCompression ………………………………… 334．1 Asymptoticequipartitionpropertyandtypicalsequences ………………………… 334．2 Losslesssourcecoding ……………………………………………………………… 344．2．1 Encoder …………………………………………………………………………… 344．2．2 Blockcode ………………………………………………………………………… 354．2．3 Fixedlengthcode………………………………………………………………… 364．2．4 Variablelengthcode …………………………………………………………… 424．3 Datacompression ……………………………………………………………………… 484．3．1 Shannoncoding ………………………………………………………………… 494．3．2 Huffmancoding ………………………………………………………………… 504．3．3 Fanocoding ……………………………………………………………………… 52Exercises ……………………………………………………………………………………… 52Chapter5 DiscreteChannelandItsCapacity ……………………………………………… 545．1 Mathematicalmodelofchannel ……………………………………………………… 545．2 Discretememorylesschannel ………………………………………………………… 555．2．1 Mathematicalmodelofdiscretememorylesschannel ………………………… 555．2．2 SimpleDMC ……………………………………………………………………… 565．2．3 Extensionofdiscretememorylesschannel …………………………………… 605．3 Channelcombination ………………………………………………………………… 655．4 Channelcapacity ……………………………………………………………………… 705．4．1 Conceptofchannelcapacity …………………………………………………… 705．4．2 Channelcapacityofseveralspecialdiscretechannels ………………………… 715．4．3 Channelcapacityofsymmetricchannels ……………………………………… 735．4．4 ChannelcapacityofextendedDMC …………………………………………… 755．4．5 ChannelcapacityofindependentparallelDMC ……………………………… 765．4．6 Channelcapacityofthesumchannel…………………………………………… 775．4．7 Channelcapacityofgeneraldiscretechannels ………………………………… 78Exercises ……………………………………………………………………………………… 79Chapter6 NoisyＧchannelCoding ……………………………………………………………… 816．1 Probabilityoferror …………………………………………………………………… 816．2 Decodingrules ………………………………………………………………………… 836．3 Channelcoding ………………………………………………………………………… 846．3．1 Simplerepetitioncode …………………………………………………………… 846．3．2 Linearcode ……………………………………………………………………… 876．4 NoisyＧchannelcodingtheorem ……………………………………………………… 91Exercises ……………………………………………………………………………………… 91Chapter7 RateDistortion …………………………………………………………………… 937．1 Quantization …………………………………………………………………………… 937．2 Distortiondefinition…………………………………………………………………… 947．2．1 Distortionfunction ……………………………………………………………… 947．2．2 MeanＧdistortion ………………………………………………………………… 957．3 Ratedistortionfunction ……………………………………………………………… 977．3．1 Fidelitycriterionforgivenchannel …………………………………………… 977．3．2 Definitionofratedistortionfunction…………………………………………… 987．3．3 Propertyofratedistortionfunction …………………………………………… 987．4 Ratedistortiontheoremandtheconverse ………………………………………… 1017．5 Thecalculationofratedistortionfunction ………………………………………… 103Exercises …………………………………………………………………………………… 105Chapter8 ContinuousSourceandItsEntropyRate ……………………………………… 1078．1 Continuoussource …………………………………………………………………… 1078．2 Entropyofcontinuoussource ……………………………………………………… 1078．3 Maximumentropyofcontinuoussource…………………………………………… 1098．4 Jointentropy,conditionalentropyandmutualinformationforcontinuousrandomvariables …………………………………………………………………… 1098．5 Entropyrateofcontinuoussource ………………………………………………… 1118．6 Ratedistortionforcontinuoussource ……………………………………………… 114Exercises …………………………………………………………………………………… 117Chapter9 ContinuousChannelandItsCapacity …………………………………………… 1199．1 Capacityofcontinuouschannel …………………………………………………… 1199．1．1 CapacityofdiscreteＧtimechannel……………………………………………… 1199．1．2 CapacityofcontinuousＧtimechannel ………………………………………… 1209．2 TheGaussianchannel ……………………………………………………………… 1219．3 BandＧlimitedchannels ……………………………………………………………… 1229．4 Codingtheoremforcontinuouschannel …………………………………………… 123Exercises …………………………………………………………………………………… 124Chapter10 MaximumEntropyandSpectrumEstimation ………………………………… 12510．1 Maximumentropyprobabilitydistribution ……………………………………… 12510．1．1 Maximumentropydistribution ……………………………………………… 12510．1．2 Examples ……………………………………………………………………… 12610．2 Maximumentropyspectrumestimation ………………………………………… 12710．2．1 Burgsmaxentropytheorem ………………………………………………… 12710．2．2 Maximumentropyspectrumestimation …………………………………… 130Exercises …………………………………………………………………………………… 137Chapter11 ExperimentsofInformationTheory …………………………………………… 13811．1 Measureofinformation …………………………………………………………… 13811．1．1 Informationcalculator ………………………………………………………… 13811．1．2 Propertiesofentropy ………………………………………………………… 13911．2 SimulationofMarkovsource ……………………………………………………… 14011．3 Performancesimulationforsourcecoding ……………………………………… 14111．3．1 Shannoncoding ……………………………………………………………… 14211．3．2 Huffmancoding ……………………………………………………………… 14311．3．3 Fanocoding …………………………………………………………………… 14411．4 SimulationofBSC ………………………………………………………………… 14411．5 Simulationofthecascadechannel ………………………………………………… 14511．6 Calculationofchannelcapacity …………………………………………………… 14811．7 Decodingrules ……………………………………………………………………… 14911．8 Performancedemonstrationofchannelcoding…………………………………… 150References ……………………………………………………………………………………… 152
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