This book explains a new generation of language-independent universal compression methods from the conceptual to the implementation level, including full details of algorithms and comprehensive performance comparisons. For courses in communication algorithms or data communications.
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achieved adaptive Huffman coding adaptive model algorithm alphabet approximate arithmetic coding ASCII binary tree blending Brown corpus bytes calculated Chapter characters cloning code space coder compression schemes conditional probabilities conditioning class context models data compression data structure described dictionary coding dictionary scheme digram distribution efficient encoder and decoder entropy enumeration error escape probability estimate example Figure finite-context models finite-state model Huffman coding implementation incremented initial model input input-output models integer letter longest match LZFG LZSS method n-gram node number of bits occur operation optimal parsing order-0 model output parameters phrases possible PPMC practice prediction prefix problem range redundancy represent rn rn sample Section sequence Shannon-Fano coding shows shutter telegraphs statistical stored string substring symbol Table techniques text compression tion transmission transmitted trie update vine pointers window words zero-frequency problem Zipf distribution Ziv-Lempel