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Book Details
Foundations of Mathematical Modeling and Analysis for Engineering is designed for first-year graduate and advanced undergraduate engineering students. The book explores linear system theory and demonstrates its application in developing analytical solutions to various equations, essential for describing physical systems through mathematical modeling. This foundation is crucial for learning and research in engineering and various scientific fields. It equips students with the mathematical tools needed to solve entire classes of linear algebraic, ordinary-, and partial-differential equations, while also teaching principles for formulating, organizing, and solving linear subsystems, all of which are vital components of both linear and nonlinear mathematical models.
This knowledge prepares students for advanced studies in engineering, applied mathematics, and foundational sciences.
Key Features
- 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
 
About the author
By A. Ted Watson, Ph.D., Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO, USA2. 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
Appendices
A. A Word on Proofs
B. Vector calculus and operations
C. Simulate measurement errors
D. Additional operations with square matrices
E. Addendum to Chapter 7
F. Higher-Order Linear ODEs
G. QR Factorization
H. Sequences and Convergence
I. Eulers Equidimensional Equation
J. Sturm-Liouville Equations
K. Bessel’s equation
L. Best linear unbiased predictions and estimates
First-year graduate engineering students across all engineering disciplines.
							









