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Applied Numerical Linear Algebra [Pehme köide]

  • Formaat: Paperback / softback, 424 pages, kaal: 776 g
  • Sari: Classics in Applied Mathematics
  • Ilmumisaeg: 28-Feb-2022
  • Kirjastus: Society for Industrial & Applied Mathematics,U.S.
  • ISBN-10: 1611976855
  • ISBN-13: 9781611976854
  • Formaat: Paperback / softback, 424 pages, kaal: 776 g
  • Sari: Classics in Applied Mathematics
  • Ilmumisaeg: 28-Feb-2022
  • Kirjastus: Society for Industrial & Applied Mathematics,U.S.
  • ISBN-10: 1611976855
  • ISBN-13: 9781611976854
Applied Numerical Linear Algebra introduces students to numerical issues that arise in linear algebra and its applications. A wide range of techniques are touched on, including direct to iterative methods, orthogonal factorizations, least squares, eigenproblems, and nonlinear equations.

Inside Applied Numerical Linear Algebra, readers will find:

Clear and detailed explanations on a wide range of topics from condition numbers to the singular value decomposition. Material on nonlinear systems as well as linear systems. Frequent illustrations using discretizations of boundary-value problems or demonstrating other concepts. Exercises with detailed solutions at the end of the book. Supplemental material available at https://bookstore.siam.org/cl87/bonus.





This textbook is appropriate for junior and senior undergraduate students and beginning graduate students 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.

Arvustused

William W. Hager is a Distinguished Professor of Mathematics at the University of Florida and co-director of the Center for Applied Optimization. He is a Fellow of the Society for Industrial and Applied Mathematics, and members of both the Mathematical Optimization Society and the American Geophysical Union. His research has focused on convergence analysis for algorithms in optimal control, the development of algorithms for solving large, sparse optimization problems including his dual active set algorithm, and related update/downdate techniques for sparse Cholesky factorizations that arise in active set methods.