Subspace

Reference:Elements of Information Theory, 2nd EditionSlides of EE4560, TUD文章目录IntroductionSlepian-Wolf CodingRandom BinningEncoding and Decoding SchemeOutline of Proof: AchievabilityInterpretation of Slepian-Wolf CodingIntroductionWe know how to enc

Reference:Elements of Information Theory, 2nd EditionSlides of EE4560, TUDContentIntroduction-Network IT FeaturesDiscrete Memoryless Multiple-Access ChannelBinary Multiplier ChannelBinary Erasure MA ChannelGaussian MA ChannelGaussian FDMA CapacityGaussi

Reference:Elements of Information Theory, 2nd EditionSlides of EE4560, TUDContentQuantizationRate-Distortion TheoryBinary SourceGaussian SourceIndependent Gaussian VariablesGaussian Sources with MemoryAchievability of R(D)R(D)R(D) for i.i.d. SourcesFor

Reference:Elements of Information Theory, 2nd EditionSlides of EE4560, TUDContentConsequences of The AEP: Data CompressionSource CodesKraft InequalityOptimal CodesBounds on the optimal code lengthShannon CodeHuffman CodeArithmetic CodingProblem descrip

Reference:Elements of Information Theory, 2nd EditionSlides of EE4560, TUD文章目录Differential EntropyGaussian ChannelsGaussian Channel CapacityBand-Limited ChannelParallel Gaussian ChannelsGaussian Channels with FeedbackDifferential EntropyWe now introdu

Reference:Elements of Information Theory, 2nd EditionSlides of EE4560, TUDContentPreliminariesJointly Typical SequencesChannel Coding TheoremChannel with FeedbackSource-Channel SeparationPreliminariesWe analyze a communication system as shown in Figur

Reference:Elements of Information Theory, 2nd EditionSlides of EE4560, TUDContentChannel Capacity DefinitionExample ChannelsBinary Symmetrical Channel (BSC)Binary Erasure Channel (BEC)Binary Asymmetric Channel (BAC/Z-Channel)Symmetric ChannelsProperties

Reference:Elements of Information Theory, 2nd EditionSlides of EE4560, TUDContentAEPTypical SetHigh-probability SetsAEPIn information theory, the analog of the law of large numbers is the asymptotic equipartition property (AEP). It is a direct consequ

Information MeasuresReference:Elements of Information Theory, 2nd EditionSlides of EE4560, TUDContentInformation MeasuresEntropyMutual InformationEntropy RatesHow to measure information? →\to→ Hartley’s approach [slides 5] →\to→ Problems?no allowance