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  • 1
    Online Resource
    Online Resource
    Markov processes and learning models / (1972)
    New York :Academic Press,
    Details
    UID:
    almahu_9949944082302882
    Format: 1 online resource (xiii, 274 pages)
    ISBN: 1-282-28974-8 , 9786612289743 , 0-08-095593-2
    Series Statement: Mathematics in science and engineering ; v. 84
    Note: Description based upon print version of record. , Front Cover; Markov Processes and Learning Models; Copyright Page; Contents; Preface; Chapter 0. Introduction; 0.1 Experiments and Models; 0.2 A General Theoretical Framework; 0.3 Overview; PART I: DISTANCE DIMINISHING MODELS; Chapter 1. Markov Processes and Random Systems with Complete Connections; 1.1 Markov Processes; 1.2 Random Systems with Complete Connections; Chapter 2. Distance Diminishing Models and Doeblin-Fortet Processes; 2.1 Distance Diminishing Models; 2.2 Transition Operators for Metric State Spaces , Chapter 3. The Theorem of Ionescu Tulcea and Marinescu, and Compact Markov Processes; 3.1 A Class of Operators; 3.2 The Theorem of Ionescu Tulcea and Marinescu; 3.3 Compact Markov Processes: Preliminaries; 3.4 Ergodic Decomposition; 3.5 Subergodic Decomposition; 3.6 Regular and Absorbing Processes; 3.7 Finite Markov Chains; Chapter 4. Distance Diminishing Models with Noncompact State Spaces; 4.1 A Condition on p; 4.2 Invariant Subsets; Chapter 5. Functions of Markov Processes; 5.1 Introduction; 5.2 Central Limit Theorem; 5.3 Estimation of pu; 5.4 Estimation of s2; 5.5 A Representation of s2 , 5.6 Asymptotic Stationarity; 5.7 Vector Valued Functions and Spectra; Chapter 6. Functions of Events; 6.1 Theprocess Xn' = (En, Xn+1); 6.2 Unbounded Functions of Several Events; PART II: SLOW LEARNING; Chapter 7. Introduction to Slow Learning; 7.1 Two Kinds of Slow Learning; 7.2 Small Probability; 7.3 Small Steps: Heuristics; Chapter 8. Transient Behavior in the Case of Large Drift; 8.1 A General Central Limit Theorem; 8.2 Properties of f(t); 8.3 Proofs of (A) and (B); 8.4 Proof of (C); 8.5 Near a Critical Point; Chapter 9. Transient Behavior in the Case of Small Drift , 9.1 Diffusion Approximation in a Bounded Interval; 9.2 Invariance; 9.3 Semigroups; Chapter 10. Steady-State Behavior; 10.1 A Limit Theorem for Stationary Probabilities; 10.2 Proof of the Theorem; 10.3 A More Precise Approximation to E(Xn?); Chapter 11. Absorption Probabilities; 11.1 Bounded State Spaces; 11.2 Unbounded State Spaces; PART III: SPECIAL MODELS; Chapter 12. The Five-Operator Linear Model; 12.1 Criteria for Regularity and Absorption; 12.2 The Mean Learning Curve; 12.3 Interresponse Dependencies; 12.4 Slow Learning; Chapter 13. The Fixed Sample Size Model , 13.1 Criteria for Regularity and Absorption13.2 Mean Learning Curve and Interresponse Dependencies; 13.3 Slow Learning; 13.4 Convergence to the Linear Model; Chapter 14. Additive Models; 14.1 Criteria for Recurrence and Absorption; 14.2 Asymptotic A1 Response Frequency; 14.3 Existence of Stationary Probabilities; 14.4 Uniqueness of the Stationary Probability; 14.5 Slow Learning; Chapter 15. Multiresponse Linear Models; 15.1 Criteria for Regularity; 15.2 The Distribution of Yn and Y8; Chapter 16. The Zeaman-House-Lovejoy Models; 16.1 A Criterion for Absorption; 16.2 Expected Total Errors; 16.3 The Overlearning Reversal Effect , English
    Additional Edition: ISBN 0-12-521450-2
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    HU Berlin
    FU Berlin
    Charité
  • 2
    Online Resource
    Online Resource
    Markov processes and learning models (1972)
    New York : Academic Press
    Details
    UID:
    gbv_1657809528
    Format: 1 online resource (xiii, 274 p.)
    Edition: Reproduktion Elsevier e-book collection on ScienceDirect
    ISBN: 0080955932 , 9780080955933 , 9780125214506
    Series Statement: Mathematics in science and engineering v. 84
    Content: Markov processes and learning models
    Note: Description based on print version record , Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.
    Additional Edition: ISBN 1282289748
    Additional Edition: Erscheint auch als Druck-Ausgabe Norman, M. Frank Markov processes and learning models New York, NY [u.a.] : Acad. Press, 1972 ISBN 0125214502
    Language: English
    Subjects: Mathematics
    RVK:
    SK 820
    Keywords: Markov-Prozess ; Mathematische Lerntheorie ; Electronic books ; Electronic books
    URL: Volltext  (Deutschlandweit zugänglich)
    URL: Volltext
    URL: lizenzpflichtig
    URL: Volltext
    URL: lizenzpflichtig
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    Online Resource
    Online Access
    Stabi Berlin
    UB Potsdam
  • 3
    Book
    Book
    Markov Processes and learning models (1972)
    New York 〈〈[u.a.]〉〉 : Acad. Pr.
    Details
    UID:
    b3kat_BV024657417
    Format: 13, 274 S.
    ISBN: 0125214502
    Series Statement: Mathematics in science and engineering 84
    Language: English
    Keywords: Markov-Prozess ; Lerntheorie ; Stochastischer Prozess
    URL: Inhaltsverzeichnis
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  • 4
    Book
    Book
    Markov processes and learning models / (1972)
    New York, NY [u.a.] :Acad. Press,
    Details
    UID:
    almafu_BV003112111
    Format: XIII, 274 S.
    ISBN: 0-12-521450-2
    Series Statement: Mathematics in science and engineering 84
    Language: English
    Subjects: Economics , Psychology , Mathematics
    RVK:
    CM 2500
    RVK:
    CP 5200
    RVK:
    QH 237
    RVK:
    SI 990
    RVK:
    SK 820
    Keywords: Markov-Prozess ; Lerntheorie ; Stochastischer Prozess
    Library Location Call Number Volume/Issue/Year Availability
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    Book
    HU Berlin get availability status
    FU Berlin get availability status
  • 5
    Book
    Book
    Markov Processes and learning models (1972)
    New York u.a. : Acad. Pr.
    Details
    UID:
    b3kat_BV024684136
    Format: 13, 274 S.
    ISBN: 0125214502
    Series Statement: Mathematics in science and engineering 84
    Language: Undetermined
    Keywords: Markov-Prozess ; Lerntheorie ; Stochastischer Prozess
    Library Location Call Number Volume/Issue/Year Availability
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    TU Berlin get availability status
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