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Probability and Information Theory

Proceedings of the International Symposium at McMaster University, Canada, April, 1968

  • Editors
  • M. Behara
  • K. Krickeberg
  • J. Wolfowitz
Conference proceedings

Part of the Lecture Notes in Mathematics book series (LNM, volume 89)

Table of contents

  1. Front Matter
    Pages N2-IV
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  2. On different characterizations of entropies
    J. Aczel
    Pages 1-11
  3. The structure of capacity functions for compound channels
    R. Ahlswede, J. Wolfowitz
    Pages 12-54
  4. Boolean algebraic methods in Markov chains
    M. Barahamihir, D. Behara
    Pages 55-63
  5. Maxima of partial sums
    Patrick Billingsley
    Pages 64-76
  6. Series expansions for random processes
    L. L. Campbell
    Pages 77-95
  7. Glivenko-Cantelli type theorems for distance functions based on the modified empirical distribution function of M. Kac and for the empirical process with random sample size in general
    Miklós Csörgő
    Pages 96-98
  8. On the continuity of Markov processes
    Taqdir Husain
    Pages 99-105
  9. Some mathematical problems in statistical mechanics
    M. Kac
    Pages 106-124
  10. Asymptotic behaviour of the average probability of error for low rates of information transmission
    N. S. Kambo, S. Kotz
    Pages 125-125
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  11. On the optimum rate of transmitting information
    J. H. B. Kemperman
    Pages 126-169
  12. A necessary and sufficient condition for the validity of the local ergodic theorem
    Ulrich Krengel
    Pages 170-177
  13. Recent results on mixing in topological measure spaces
    K. Krickeberg
    Pages 178-185
  14. Convergence in probability and allied results
    A. R. Padmanabhan
    Pages 186-186
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  15. Applications of almost surely convergent constructions of weakly convergent processes
    Ronald Pyke
    Pages 187-200
  16. Random processes defined through the interaction of an infinite particle system
    Frank Spitzer
    Pages 201-223
  17. The central limit theorem and ε-entropy
    Volker Strassen, R.M. Dudley
    Pages 224-231
  18. Maximum probability estimators with a general loss function
    L. Weiss, J. Wolfowitz
    Pages 232-256
  19. Back Matter
    Pages 257-259
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About these proceedings

Keywords

Boolean algebra Ergodic theory Informationstheorie Markov chain Markov process Probability Wahrscheinlichkeitsrechnung entropy information information theory mixing

Bibliographic information

  • DOI https://doi.org/10.1007/BFb0079113
  • Copyright Information Springer-Verlag Berlin Heidelberg 1969
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-04608-0
  • Online ISBN 978-3-540-36098-8
  • Series Print ISSN 0075-8434
  • Series Online ISSN 1617-9692
  • Buy this book on publisher's site