Foundations of Mathematical Modeling and Analysis in Engineering
Will be published approx. on 11. December 2025
Book
Paperback/Softback
400 pages
978-0-443-29592-8 (ISBN)
Description
Foundations of Mathematical Modeling and Analysis in Engineering offers a comprehensive
presentation of the mathematical principles underpinning modern engineering and the quantitative sciences, and develops mathematical modeling as a foundational intellectual discipline. Designed for graduate and advanced undergraduate students, and accessible to seasoned professionals, it provides the means to develop and employ mathematical representations of physical processes and systems.
presentation of the mathematical principles underpinning modern engineering and the quantitative sciences, and develops mathematical modeling as a foundational intellectual discipline. Designed for graduate and advanced undergraduate students, and accessible to seasoned professionals, it provides the means to develop and employ mathematical representations of physical processes and systems.
More details
Language
English
Place of publication
Woburn
United States
Publishing group
Elsevier - Health Sciences Division
Target group
College/higher education
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 232 mm
Width: 190 mm
Thickness: 22 mm
Weight
658 gr
ISBN-13
978-0-443-29592-8 (9780443295928)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
E-Book
12/2025
Elsevier
€73.99
Available for download
Person
Professor Emeritus A. Ted Watson holds a BS from University of Texas at Austin and a PhD from California Institute of Technology, both in chemical engineering. He attained the position of Professor at Texas A&M University (TAMU) before joining Colorado State University (CSU) as the founding department head of chemical & biological engineering. He has advanced mathematical modeling and system and parameter identification while working within a variety of fields. He established the Engineering Imaging Laboratory at TAMU and Rocky Mountain Magnetic Resonance at CSU and was elected Fellow of the American Institute of Chemical Engineers (AIChE).
Content
1. Introduction
2. Mathematical representations of physical phenomena
3. Solving linear algebraic equations
4. Vector spaces and their representations
5. Linear transformations and representations
6. Inner product spaces
7. Operators and matrix representations
8. Ordinary differential equations
9. Function representation and transforms
10. Partial differential equations
11. System and parameter identification
2. Mathematical representations of physical phenomena
3. Solving linear algebraic equations
4. Vector spaces and their representations
5. Linear transformations and representations
6. Inner product spaces
7. Operators and matrix representations
8. Ordinary differential equations
9. Function representation and transforms
10. Partial differential equations
11. System and parameter identification