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On Sequential Discrimination Between Close Markov Chains

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General Theory of Information Transfer and Combinatorics

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4123))

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Abstract

The appropriateness of the Wald-type logarithmic asymptotics for the mean length of sequential discrimination strategies between close alternatives has been already challenged in the well-known controversy over comparative performances of the asymptotically optimal Chernoff’s discrimination strategies and ad hoc heuristic rules of Box and Hill in the seventies.

We continue this discussion by showing a poor performance of the Wald-type asymptotic bounds for the mean length of asymptotically optimal sequential discrimination strategies between the simplest types of Markov chains by simulation. We propose some weak remedies against this disaster and some alternative asymptotic tools.

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References

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Authors
  1. M. B. Malyutov
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  2. D. M. Malyutov
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Editor information

Editors and Affiliations

  1. Fakultät für Mathematik, Universität Bielefeld, 100131, 33501, Bielefeld, Germany

    Rudolf Ahlswede

  2. Fakultät für Mathematik, Universität Bielefeld, Universitätsstr. 25, 33615, Bielefeld, Germany

    Lars Bäumer , Ning Cai , Harout Aydinian  & Christian Deppe , ,  & 

  3. Russian Academy of Sciences Institute of Problems of Information Transmission, Bol’shoi Karetnyi per. 19, 101447, Moscow, Russia

    Vladimir Blinovsky

  4. Universität Bielefeld, Fakultät für Mathematik, Universitätsstr. 25, 33615, Bielefeld, Germany

    Haik Mashurian

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© 2006 Springer-Verlag Berlin Heidelberg

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Malyutov, M.B., Malyutov, D.M. (2006). On Sequential Discrimination Between Close Markov Chains. In: Ahlswede, R., et al. General Theory of Information Transfer and Combinatorics. Lecture Notes in Computer Science, vol 4123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11889342_30

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  • DOI: https://doi.org/10.1007/11889342_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46244-6

  • Online ISBN: 978-3-540-46245-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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