Linear Algebra and Linear Operators in Engineering

With Applications in Mathematica®

By

  • H. Davis, University of Minnesota, Minneapolis, U.S.A.
  • Kendall Thomson, Purdue University, West Lafayette, Indiana, U.S.A.

Designed for advanced engineering, physical science, and applied mathematics students, this innovative textbook is an introduction to both the theory and practical application of linear algebra and functional analysis. The book is self-contained, beginning with elementary principles, basic concepts, and definitions. The important theorems of the subject are covered and effective application tools are developed, working up to a thorough treatment of eigenanalysis and the spectral resolution theorem. Building on a fundamental understanding of finite vector spaces, infinite dimensional Hilbert spaces are introduced from analogy. Wherever possible, theorems and definitions from matrix theory are called upon to drive the analogy home. The result is a clear and intuitive segue to functional analysis, culminating in a practical introduction to the functional theory of integral and differential operators. Numerous examples, problems, and illustrations highlight applications from all over engineering and the physical sciences. Also included are several numerical applications, complete with Mathematica solutions and code, giving the student a "hands-on" introduction to numerical analysis. Linear Algebra and Linear Operators in Engineering is ideally suited as the main text of an introductory graduate course, and is a fine instrument for self-study or as a general reference for those applying mathematics.
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Audience

Students in graduate level applied mathematics courses in engineering departments (particularly chemical engineering), and practicing engineers.

 

Book information

  • Published: June 2000
  • Imprint: ACADEMIC PRESS
  • ISBN: 978-0-12-206349-7


Table of Contents

Preface. Determinants. Vectors and Matrices. Solution of Linear and Nonlinear Systems. General Theory of Solvability of Linear. The Eigenproblem. Perfect Matrices. Imperfect or Defective Matrices. Infinite-Dimensional Linear Vector Spaces. Linear Integral Operators in a Hilbert Space. Linear Differential Operators in a Hilbert Space. Appendix. Index