信息理论基础-(英文版)

内容简介

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　　Thisbooksystematicallyintroducedthefundamentalsofinformationtheory,focusingonthebasicmodelofcommunicationsystems．Itconsistsof11Chapters,includingtwoparts,namely,basicconceptionsofinforＧmationtheoryandrelatedapplicationsofinformationtheory．Thefirstpartcontainsstatisticalmeasureofinformation,discretesource,losslesssourcecodinganddatacompression,discretechannelanditscapacity,channelcoding,whilethesecondpartincludesratedistortion,continuoussource,continuouschannelanditscapacity,maximumentropyandspectrumestimationaswellascomputersimulationexperimentsrelevanttoinformationtheory．　　Thisbooksummarizedtheexperienceoftheauthorsonteachinginformationcoursein EnglishandChinese,togetherwiththeirunderstandingsfromyearsscientificresearchpractice．Itcanbeusedasteachingmaterialoninformationtheorycourseforbothinternationalundergraduateandgraduatestudents．

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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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书名:信息理论基础-(英文版)

作者:陈杰

页数:153

定价:¥29.0

出版社:北京航空航天大学出版社

出版日期:2016-01-01

ISBN:9787512419728

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