Stochastic Differential Equations for Science and Engineering

This book provides a comprehensive introduction to stochastic differential equations for science and engineering students, covering the mathematical construction, applications, and computational aspects. It includes examples, exercises, and a GitHub repository with code and solutions.

Format: Hardback
Length: 366 pages
Publication date: 15 June 2023
Publisher: Taylor & Francis Ltd

Stochastic Differential Equations for Science and Engineering is a comprehensive textbook designed for advanced students pursuing M.Sc. and Ph.D. degrees in the fields of science and engineering. The book offers a detailed mathematical framework for constructing stochastic differential equations, catering to the audience's level of expertise. It delves into various applications, including estimation, stability analysis, and control, providing practical insights into these subjects.

To enhance the learning experience, the book is accompanied by a comprehensive GitHub repository. This repository contains a toolbox in R, which implements the algorithms described in the book. It also includes code that regenerates all figures and provides solutions to challenging exercises.

The book's features include:

Numerous Exercises: The book is packed with a wide range of exercises, designed to reinforce the concepts learned and test the reader's understanding. These exercises cover various topics, including the construction of stochastic differential equations, their solutions, and applications.

Suitable for Science and Engineering Students: Whether you are a science or engineering student, this textbook offers a thorough treatment of the mathematical theory combined with an accessible treatment of motivating examples. It provides a solid foundation for understanding and applying stochastic differential equations in your future research and professional endeavors.

Thorough Treatment of the Mathematical Theory: The book covers the fundamental principles of stochastic differential equations, including stochastic processes, martingales, and differential equations with stochastic coefficients. It provides a comprehensive understanding of the mathematical tools required to analyze and solve these equations.

Accessible Treatment of Motivating Examples: The author incorporates real-world examples and applications to illustrate the theoretical concepts and make them more relatable to the reader. These examples help to clarify the theoretical discussions and provide practical insights into the practical applications of stochastic differential equations.

GitHub Repository: The GitHub repository accompanying the book offers additional resources and support. It includes a toolbox in R, which implements the algorithms described in the book. It also includes code that regenerates all figures and provides solutions to challenging exercises.

By utilizing this textbook and the accompanying GitHub repository, students can gain a deep understanding of stochastic differential equations and their applications in science and engineering. The book's clear and concise writing style, coupled with the extensive exercises and examples, makes it an invaluable resource for advanced students seeking to excel in this field.

Weight: 678g
Dimension: 161 x 241 x 28 (mm)
ISBN-13: 9781032232171