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9780898716337 Academic Inspection Copy

Applied Stochastic Processes and Control for Jump-Diffusions

Modeling, Analysis, and Computation
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This self-contained, practical, entry-level text integrates the basic principles of applied mathematics, applied probability, and computational science for a clear presentation of stochastic processes and control for jump-diffusions in continuous time. The author covers the important problem of controlling these systems and, through the use of a jump calculus construction, discusses the strong role of discontinuous and nonsmooth properties versus random properties in stochastic systems. The book emphasizes modeling and problem solving and presents sample applications in financial engineering and biomedical modeling. Computational and analytic exercises and examples are included throughout. While classical applied mathematics is used in most of the chapters to set up systematic derivations and essential proofs, the final chapter bridges the gap between the applied and the abstract worlds to give readers an understanding of the more abstract literature on jump-diffusions. An additional 160 pages of online appendices are available on a Web page that supplements the book.
Floyd B. Hanson is Professor Emeritus in the Department of Mathematics, Statistics, and Computer Science at the University of Illinois, Chicago. He received the Premier UIC Award for Excellence in Teaching for 2001 and has published approximately 100 research papers.
List of Figures List of Tables Preface Chapter 1. Stochastic Jump and Diffusion Processes: Introduction Chapter 2. Stochastic Integration for Diffusions Chapter 3. Stochastic Integration for Jumps Chapter 4. Stochastic Calculus for Jump-Diffusions: Elementary SDEs Chapter 5. Stochastic Calculus for General Markov SDEs: Space-Time Poisson, State-Dependent Noise, and Multidimensions Chapter 6. Stochastic Optimal Control: Stochastic Dynamic Programming Chapter 7. Kolmogorov Forward and Backward Equations and Their Applications Chapter 8. Computational Stochastic Control Methods Chapter 9. Stochastic Simulations Chapter 10. Applications in Financial Engineering Chapter 11. Applications in Mathematical Biology and Medicine Chapter 12. Applied Guide to Abstract Theory of Stochastic Processes Bibliography Index A. Online Appendix: Deterministic Optimal Control B. Online Appendix: Preliminaries in Probability and Analysis C. Online Appendix: MATLAB Programs;
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