Foundations of Mathematical Modeling and Analysis in Engineering
Autor A. Ted Watsonen Limba Engleză Paperback – 11 dec 2025
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.
- A comprehensive toolbox for graduate engineering students, covering foundational and advanced mathematical concepts and methods
- Emphasizes real-world applications of mathematical models, bolstering problem-solving skills through worked examples and end-of-chapter exercises
- Aids the transition from undergraduate to graduate studies, ensuring comprehensive understanding and application of the mathematical concepts for advanced engineering courses and research
- Offers teaching support, including an image bank, and full Solutions Manual, for qualified instructors, available for request at https://educate.elsevier.com/9780443295928
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Specificații
ISBN-13: 9780443295928
ISBN-10: 0443295921
Pagini: 400
Dimensiuni: 191 x 235 mm
Editura: ELSEVIER SCIENCE
ISBN-10: 0443295921
Pagini: 400
Dimensiuni: 191 x 235 mm
Editura: ELSEVIER SCIENCE
Cuprins
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