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The Less Is More Linear Algebra of Vector Spaces and Matrices (Paperback) Loot Price: R1,753
Discovery Miles 17 530
You Save: R140 (7%)
The Less Is More Linear Algebra of Vector Spaces and Matrices (Paperback): Daniela Calvetti, Erkki Somersalo

The Less Is More Linear Algebra of Vector Spaces and Matrices (Paperback)

Daniela Calvetti, Erkki Somersalo

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Was R1,893 Loot Price R1,753 Discovery Miles 17 530 | Repayment Terms: R164 pm x 12* You Save R140 (7%)

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Designed for a proof-based course on linear algebra, this rigorous and concise textbook intentionally introduces vector spaces, inner products, and vector and matrix norms before Gaussian elimination and eigenvalues so students can quickly discover the singular value decomposition (SVD)-arguably the most enlightening and useful of all matrix factorizations. Gaussian elimination is then introduced after the SVD and the four fundamental subspaces and is presented in the context of vector spaces rather than as a computational recipe. This allows the authors to use linear independence, spanning sets and bases, and the four fundamental subspaces to explain and exploit Gaussian elimination and the LU factorization, as well as the solution of overdetermined linear systems in the least squares sense and eigenvalues and eigenvectors. This unique textbook also includes examples and problems focused on concepts rather than the mechanics of linear algebra. The problems at the end of each chapter and in an associated website encourage readers to explore how to use the notions introduced in the chapter in a variety of ways. Additional problems, quizzes, and exams will be posted on an accompanying website and updated regularly. The Less Is More Linear Algebra of Vector Spaces and Matrices is for students and researchers interested in learning linear algebra who have the mathematical maturity to appreciate abstract concepts that generalize intuitive ideas. The early introduction of the SVD makes the book particularly useful for those interested in using linear algebra in applications such as scientific computing and data science. It is appropriate for a first proof-based course in linear algebra.

General

Imprint: Society For Industrial & Applied Mathematics,U.S.
Country of origin: United States
Release date: December 2022
Authors: Daniela Calvetti • Erkki Somersalo
Format: Paperback
Pages: 225
ISBN-13: 978-1-61197-739-4
Categories: Books > Computing & IT > General theory of computing > Mathematical theory of computation
Books > Computing & IT > General theory of computing > Data structures
Books > Computing & IT > Computer programming > Algorithms & procedures
Books > Science & Mathematics > Mathematics > Optimization > General
Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers
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LSN: 1-61197-739-8
Barcode: 9781611977394

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