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Markov Processes and Learning Models

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Author(s): M. Frank Norman (Eds.)
Series: Mathematics in Science and Engineering 84
Publisher: Academic Press
Year: 1972

Language: English
Pages: iii-xiii, 1-274

Content:
Edited by
Page iii

Copyright page
Page iv

Dedication
Page v

Preface
Pages xi-xiii

0 Introduction
Pages 1-17

1 Markov Processes and Random Systems with Complete Connections
Pages 21-29

2 Distance Diminishing Models and Doeblin-Fortet Processes
Pages 30-42

3 The Theorem of Ionescu Tulcea and Marinescu, and Compact Markov Processes
Pages 43-65

4 Distance Diminishing Models with Noncompact State Spaces
Pages 66-72

5 Functions of Markov Processes
Pages 73-97

6 Functions of Events
Pages 98-105

7 Introduction to Slow Learning
Pages 109-115

8 Transient Behavior in the Case of Large Drift
Pages 116-136

9 Transient Behavior in the Case of Small Drift
Pages 137-151

10 Steady-State Behavior
Pages 152-162

11 Absorption Probabilities
Pages 163-171

12 The Five-Operator Linear Model
Pages 175-194

13 The Fixed Sample Size Model
Pages 195-208

14 Additive Models
Pages 209-224

15 Multiresponse Linear Models
Pages 225-233

16 The Zeaman-House-Lovejoy Models
Pages 234-243

17 Other Learning Models
Pages 244-256

18 Diffusion Approximation in a Genetic Model and a Physical Model
Pages 257-262

References
Pages 263-267

List of Symbols
Pages 269-270

Index
Pages 271-274