Linear Algebra Vector Spaces Matrices (46 results)

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Paperback. Condition: New. 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.…

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Hardcover. Condition: Very Good. 222 p. 25 cm. ; LCCN: 70-116776 ; OCLC: 87645 ; LC: QA251; Dewey: 512/.897 ; blue cloth with gold lettering ; no dustjacket ; name on front endpaper ; Contents: Preliminary topics -- Vector spaces -- The Vector space V3 -- Subspaces -- Linear combination s -- Dimension -- Simultaneous equations -- Determinants -- Linear transformations -- Matrix representations of transformations -- Matrix algebra -- Inverse transformations and matrices -- Equivalent and similar matrices -- Special matrix forms: Linear functionals, Dual space, Transpose transformations, Properties of T prime, Transpose matrices, Determinants of transpose matrices, Symmetric matrices, Skew-Symmetric matrices, Characteristic vectors of symmetric matrices. ; VG. Book. …

Condition: New. 2023. paperback. . . . . .

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Paperback. Condition: new. Paperback. 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. 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 useful of all matrix factorizations. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This uniquetext provides a geometric approach to group theory and linear algebra, bringing to light the interesting ways in which these subjects interact. Requiring few prerequisites beyond understanding the notion of a proof, the text aims to give students a strong foundation in both geometry and algebra.Starting with preliminaries (relations, elementary combinatorics, and induction), the book then proceeds to the core topics: the elements of the theory of groups and fields (Lagrange's Theorem, cosets, the complex numbers and the prime fields), matrix theory and matrix groups, determinants, vector spaces, linear mappings, eigentheory and diagonalization, Jordan decomposition and normal form, normal matrices, and quadratic forms. The final two chapters consist of a more intensive look at group theory, emphasizing orbit stabilizer methods, and an introduction to linear algebraic groups, which enriches the notion of a matrix group. Applications involving symmetry groups, determinants, linear coding theory and cryptography are interwoven throughout. Each section ends with ample practice problems assisting the reader to better understand the material.Some of the applications are illustrated in the chapter appendices.The author's unique melding of topics evolved from a two semester course that he taught at the University of British Columbia consisting of an undergraduate honors course on abstract linear algebra and a similar course on the theory of groups. The combined content from both makes this rare text ideal for a year-long course, covering more material than most linear algebra texts. It is also optimal for independent study and as a supplementary text for various professional applications. Advanced undergraduate or graduate students in mathematics, physics, computer science and engineering will find this book both useful and enjoyable.…

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This textbook provides a clear, systematic, and university-level introduction to linear algebra and analytic geometry. It covers the central topics of the early university curriculum, including vector spaces, linear mappings, matrices, determinants, eigenvalue theory, and Euclidean and unitary vector spaces. The mathematical theory is developed precisely and in a logically structured way, with all major results fully proved. At the same time, the didactically clear presentation ensures that even demanding content remains accessible and easy to follow. Numerous examples, exercises, and fully worked solutions support understanding, enable effective exam preparation, and make the book well suited for independent study. This book is ideal for students of mathematics, computer science, physics, engineering, and related fields.…

Taschenbuch. Condition: Neu. Linear Algebra and Analytic Geometry | Linear Mappings, Matrices, Determinants, Eigenvalue Theory, and Euclidean and Unitary Vector [.] | Lucien Sina | Taschenbuch | Englisch | epubli | EAN 9783565450374 | Verantwortliche Person für die EU: Neopubli GmbH (Imprint: epubli), Köpenicker Str. 154a, 10997 Berlin, produktsicherheit[at]epubli[dot]com | Anbieter: preigu. …

Paperback. Condition: Brand New. reprint edition. 427 pages. 9.25x6.10x1.54 inches. In Stock.