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Starting with an introduction to vectors, matrices, and linear transformations, the book focuses on building a geometric intuition of what these tools represent. Linear systems offer a powerful application of the ideas seen so far, and lead onto the introduction of subspaces, linear independence, bases, and rank. Investigation then focuses on the algebraic properties of matrices that illuminate the geometry of the linear transformations that they represent. Determinants, eigenvalues, and eigenvectors all benefit from this geometric viewpoint. Throughout, ¿Extra Topic¿ sections augment the core content with a wide range of ideas and applications, from linear programming, to power iteration and linear recurrence relations. Exercises of all levels accompany each section, including many designed to be tackled using computer software.
Introduction to Linear and Matrix Algebra is ideal for an introductory proof-based linear algebra course. The engaging color presentation and frequent marginal notes showcase the author¿s visual approach. Students are assumed to have completed one or two university-level mathematics courses, though calculus is not an explicit requirement. Instructors will appreciate the ample opportunities to choose topics that align with the needs of each classroom, and the online homework sets that are available through WeBWorK.
Starting with an introduction to vectors, matrices, and linear transformations, the book focuses on building a geometric intuition of what these tools represent. Linear systems offer a powerful application of the ideas seen so far, and lead onto the introduction of subspaces, linear independence, bases, and rank. Investigation then focuses on the algebraic properties of matrices that illuminate the geometry of the linear transformations that they represent. Determinants, eigenvalues, and eigenvectors all benefit from this geometric viewpoint. Throughout, ¿Extra Topic¿ sections augment the core content with a wide range of ideas and applications, from linear programming, to power iteration and linear recurrence relations. Exercises of all levels accompany each section, including many designed to be tackled using computer software.
Introduction to Linear and Matrix Algebra is ideal for an introductory proof-based linear algebra course. The engaging color presentation and frequent marginal notes showcase the author¿s visual approach. Students are assumed to have completed one or two university-level mathematics courses, though calculus is not an explicit requirement. Instructors will appreciate the ample opportunities to choose topics that align with the needs of each classroom, and the online homework sets that are available through WeBWorK.
Nathaniel Johnston is an Associate Professor of Mathematics at Mount Allison University in New Brunswick, Canada. His research makes use of linear algebra, matrix analysis, and convex optimization to tackle questions related to the theory of quantum entanglement. His companion volume, Advanced Linear and Matrix Algebra, is also published by Springer.
Motivates the study of linear algebra by exploring the interplay between algebra and geometry
Engages readers with a visual approach that uses color to enhance both content and learning
Features a wide selection of theoretical and applied topics to complement the core material
Incorporates exercises of all levels, including many designed for computer software
Offers corresponding online homework sets through WeBWorK
Includes supplementary material: [...]
Erscheinungsjahr: | 2021 |
---|---|
Fachbereich: | Arithmetik & Algebra |
Genre: | Mathematik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Inhalt: |
xvi
482 S. 38 s/w Illustr. 286 farbige Illustr. 482 p. 324 illus. 286 illus. in color. |
ISBN-13: | 9783030528102 |
ISBN-10: | 3030528103 |
Sprache: | Englisch |
Ausstattung / Beilage: | HC runder Rücken kaschiert |
Einband: | Gebunden |
Autor: | Johnston, Nathaniel |
Auflage: | 1st ed. 2021 |
Hersteller: |
Springer International Publishing
Springer International Publishing AG |
Maße: | 260 x 183 x 31 mm |
Von/Mit: | Nathaniel Johnston |
Erscheinungsdatum: | 20.05.2021 |
Gewicht: | 1,241 kg |
Nathaniel Johnston is an Associate Professor of Mathematics at Mount Allison University in New Brunswick, Canada. His research makes use of linear algebra, matrix analysis, and convex optimization to tackle questions related to the theory of quantum entanglement. His companion volume, Advanced Linear and Matrix Algebra, is also published by Springer.
Motivates the study of linear algebra by exploring the interplay between algebra and geometry
Engages readers with a visual approach that uses color to enhance both content and learning
Features a wide selection of theoretical and applied topics to complement the core material
Incorporates exercises of all levels, including many designed for computer software
Offers corresponding online homework sets through WeBWorK
Includes supplementary material: [...]
Erscheinungsjahr: | 2021 |
---|---|
Fachbereich: | Arithmetik & Algebra |
Genre: | Mathematik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Inhalt: |
xvi
482 S. 38 s/w Illustr. 286 farbige Illustr. 482 p. 324 illus. 286 illus. in color. |
ISBN-13: | 9783030528102 |
ISBN-10: | 3030528103 |
Sprache: | Englisch |
Ausstattung / Beilage: | HC runder Rücken kaschiert |
Einband: | Gebunden |
Autor: | Johnston, Nathaniel |
Auflage: | 1st ed. 2021 |
Hersteller: |
Springer International Publishing
Springer International Publishing AG |
Maße: | 260 x 183 x 31 mm |
Von/Mit: | Nathaniel Johnston |
Erscheinungsdatum: | 20.05.2021 |
Gewicht: | 1,241 kg |