Now in its second edition, Probabilistic Models for Dynamical Systems expands on the subject of probability theory. Written as an extension to its predecessor, this revised version introduces students to the randomness in variables and time dependent functions, and allows them to solve governing equations.
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Introduces probabilistic modeling and explores applications in a wide range of engineering fields
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Identifies and draws on specialized texts and papers published in the literature
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Develops the theoretical underpinnings and covers approximation methods and numerical methods
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Presents material relevant to students in various engineering disciplines as well as professionals in the field
This book provides a suitable resource for self-study and can be used as an all-inclusive introduction to probability for engineering. It presents basic concepts, presents history and insight, and highlights applied probability in a practical manner. With updated information, this edition includes new sections, problems, applications, and examples. Biographical summaries spotlight relevant historical figures, providing life sketches, their contributions, relevant quotes, and what makes them noteworthy. A new chapter on control and mechatronics, and over 300 illustrations rounds out the coverage.
Preface
Chapter 1 : Applications
Chapter 2 : Events and Probability
Chapter 3 : Random Variable Models
Chapter 4 : Functions of Random Variables
Chapter 5 : Random Processes
Chapter 6 : Single Degree-of-Freedom Vibration
Chapter 7 : Multi Degree-of-Freedom Vibration
Chapter 8 : Continuous System Vibration
Chapter 9 : Reliability
Chapter 10 : Nonlinear and Stochastic Dynamic Models
Chapter 11 : Non-stationary Models
Chapter 12 : Monte Carlo Methods
Chapter 13 : Fluid-Induced Vibration
Chapter 14 : Probabilistic Models in Controls and Mechatronic Systems
Index
