Coding and Information TheoryPrentice-Hall, 1986 - 259페이지 Focusing on both theory and practical applications, this volume combines in a natural way the two major aspects of information representation--representation for storage (coding theory) and representation for transmission (information theory). |
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a₁ arbitrarily average code length b₁ bandwidth binary digits binary symmetric channel block code bound channel capacity Chapter code book code word coding theory coefficients column conditional entropy correct corresponding decoding tree detection distribution double-error encoded message entropy function equation error-correcting codes error-detecting code example Exercises Figure frequency Gibbs inequality given Gray code Hamming codes hence Huffman code I(a₁ information theory input symbols instantaneous code integral joint entropy Kraft inequality log2 loge Markov process matrix maximum means message positions modulus polynomial mutual information nth extension number of 1's occur octal original p(a₁ P(ba p(Si p₁ parity check possible prime polynomial probability radius radix received message receiving end Section sent Shannon-Fano coding signaling system simple single error single-error-correcting source alphabet source symbols sphere storage Suppose syndrome term theorem uniquely decodable variable white noise zero λη