Modeling and Analysis of Stochastic Systems
eBook - PDF

Modeling and Analysis of Stochastic Systems

  1. 584 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Modeling and Analysis of Stochastic Systems

About this book

Building on the author's more than 35 years of teaching experience, Modeling and Analysis of Stochastic Systems, Third Edition, covers the most important classes of stochastic processes used in the modeling of diverse systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models.

The third edition has been updated with several new applications, including the Google search algorithm in discrete time Markov chains, several examples from health care and finance in continuous time Markov chains, and square root staffing rule in Queuing models. More than 50 new exercises have been added to enhance its use as a course text or for self-study. The sequence of chapters and exercises has been maintained between editions, to enable those now teaching from the second edition to use the third edition.

Rather than offer special tricks that work in specific problems, this book provides thorough coverage of general tools that enable the solution and analysis of stochastic models. After mastering the material in the text, readers will be well-equipped to build and analyze useful stochastic models for real-life situations.

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Yes, you can access Modeling and Analysis of Stochastic Systems by Vidyadhar G. Kulkarni in PDF and/or ePUB format, as well as other popular books in Business & Operazioni. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Chapman and Hall/CRC
Year
2016
eBook ISBN
9781498756624
Edition
3
Topic
Business
Subtopic
Operazioni
Index
Business

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Dedication
  6. Table of Contents
  7. Preface
  8. 1: Introduction
  9. 2: Discrete-TimeMarkov Chains: Transient Behavior
  10. 3: Discrete-TimeMarkov Chains: First Passage Times
  11. 4: Discrete-TimeMarkov Chains: Limiting Behavior
  12. 5: Poisson Processes
  13. 6: Continuous-Time Markov Chains
  14. 7: Queueing Models
  15. 8: Renewal Processes
  16. 9: Markov Regenerative Processes
  17. 10: Diffusion Processes
  18. Epilogue
  19. Appendix A Probability of Events
  20. Appendix B Univariate Random Variables
  21. Appendix C Multivariate Random Variables
  22. Appendix D Generating Functions
  23. Appendix E Laplace–Stieltjes Transforms
  24. Appendix F Laplace Transforms
  25. Appendix G Modes of Convergence
  26. Appendix H Results from Analysis
  27. Appendix I Difference and Differential Equations
  28. Answers to Selected Problems
  29. References
  30. INDEX