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Coding for Discrete Markov Sources

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Coding for Markov Sources

Part of the book series: International Centre for Mechanical Sciences ((CISM,volume 110))

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Abstract

Consider a finite Markov chain φ having K states \({J_1},{J_2}, \ldots ,{J_k}\) and defined by the initial probability distribution

$${\Pi _0} = {\left[ {{P_1} \cdots {P_k}} \right]^{\left. + \right)}}$$
(3.1)

and by the transition probability matrix

$$\Pi = \left[ {\begin{array}{*{20}{c}} {{{\text{P}}_{{\text{11}}}}{{\text{P}}_{{\text{12}}}} \cdots {{\text{P}}_{{\text{1k}}}}} \\ {{{\text{p}}_{{\text{k1}}}}{{\text{p}}_{{\text{k}}2}} \cdots {{\text{p}}_{{\text{kk}}}}} \end{array}} \right].$$
(3.2)

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© 1971 Springer-Verlag Wien

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Longo, G. (1971). Coding for Discrete Markov Sources. In: Coding for Markov Sources. International Centre for Mechanical Sciences, vol 110. Springer, Vienna. https://doi.org/10.1007/978-3-7091-2961-6_4

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  • DOI: https://doi.org/10.1007/978-3-7091-2961-6_4

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-81154-2

  • Online ISBN: 978-3-7091-2961-6

  • eBook Packages: Springer Book Archive

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