Uffe Høgsbro Thygesen

Stochastic Differential Equations for Science and Engineering

• Gebundenes Buch

Produktbeschreibung

Stochastic Differential Equations for Science and Engineering is aimed at students at the M.Sc. and PhD level. The book describes the mathematical construction of stochastic differential equations with a level of detail suitable to the audience, while also discussing applications to estimation, stability analysis, and control. The book includes numerous examples and challenging exercises. Computational aspects are central to the approach taken in the book, so the text is accompanied by a repository on GitHub containing a toolbox in R which implements algorithms described in the book, code that regenerates all figures, and solutions to exercises.

Features:

Contains numerous exercises, examples, and applicationsSuitable for science and engineering students at Master's or PhD level Thorough treatment of the mathematical theory combined with an accessible treatment of motivating examplesGitHub repository available at: https://github.com/Uffe-H-Thygesen/SDEbook and https://github.com/Uffe-H-Thygesen/SDEtools

Produktdetails

• Verlag: Chapman and Hall/CRC / Taylor & Francis
• Seitenzahl: 366
• Erscheinungstermin: 15. Juni 2023
• Englisch
• Abmessung: 234mm x 156mm x 22mm
• Gewicht: 679g
• ISBN-13: 9781032232171
• ISBN-10: 103223217X
• Artikelnr.: 67402164

Autorenporträt

Uffe Høgsbro Thygesen received his Ph.D. degree from the Technical University of Denmark in 1999, based on a thesis on stochastic control theory. He worked with applications to marine ecology and fisheries until 2017, where he joined the Department of Applied Mathematics and Computer Science at the same university. His research interests are centered on deterministic and stochastic dynamic systems and involve times series analysis, control, and dynamic games, primarily with applications in life science. In his spare time he teaches sailing and kayaking and learns guitar and photography.

Inhaltsangabe

Introduction. Section I. Fundamentals. 2. Diffusive Transport and Random Walks. 3. Stochastic Experiments and Probability Spaces. 4. Brownian Motion. 5. Linear Dynamic Systems. Section II Stochastic Calculus. 6. Stochastic Integrals. 7. The Stochastic Chain Rule. 8. Existence, Uniqueness, And Numerics. 9. The Kolmogorov Equations. Section III. Applications. 10. State Estimation. 11. Expectations to The Future. 12. Stochastic Stability Theory. 13. Dynamic Optimization. 14. Perspectives.