Introduction to Numerical Linear Algebra
Published on 30. March 2022
Book
Paperback/Softback
277 pages
978-1-61197-691-5 (ISBN)
Description
Fit for students just starting to build a background in mathematics, this textbook provides an introduction to numerical methods for linear algebra problems.
Introduction to Numerical Linear Algebra
is ideal for a flipped classroom, as it provides detailed explanations that allow students to read on their own and instructors to go beyond lecturing,
assumes that the reader has taken a course on linear algebra, but reviews background as needed, and
covers several topics not commonly addressed in related introductory books, including diffusion, a toy model of computed tomography, global positioning systems, the use of eigenvalues in analyzing stability of equilibria, a detailed derivation and careful motivation of the QR method for eigenvalues starting from power iteration, a discussion of the use of the SVD for assigning grades, and multigrid methods.
This textbook is appropriate for undergraduate and beginning graduate students in mathematics and related fields. It can be used in the following courses: Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory
Introduction to Numerical Linear Algebra
is ideal for a flipped classroom, as it provides detailed explanations that allow students to read on their own and instructors to go beyond lecturing,
assumes that the reader has taken a course on linear algebra, but reviews background as needed, and
covers several topics not commonly addressed in related introductory books, including diffusion, a toy model of computed tomography, global positioning systems, the use of eigenvalues in analyzing stability of equilibria, a detailed derivation and careful motivation of the QR method for eigenvalues starting from power iteration, a discussion of the use of the SVD for assigning grades, and multigrid methods.
This textbook is appropriate for undergraduate and beginning graduate students in mathematics and related fields. It can be used in the following courses: Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory
More details
Series
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Weight
735 gr
ISBN-13
978-1-61197-691-5 (9781611976915)
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Schweitzer Classification
Person
Christoph Boergers is a Professor of Mathematics at Tufts University. He has worked in and written about several areas of applied mathematics, including numerical methods for elliptic boundary value problems, computational fluid dynamics, computational methods for linear particle transport, computational neuroscience, the mathematics of voting, and anomalous diffusion and Levy walks. He is the author of two previous books, including Mathematics of Social Choice (SIAM, 2009). He has been a SIAM member for much of his life.