Advanced Linear and Matrix Algebra - Nathaniel Johnston

Advanced Linear and Matrix Algebra

Buch | Softcover
XVI, 494 Seiten
2022
Springer International Publishing (Verlag)
978-3-030-52817-1 (ISBN)
58,84 inkl. MwSt

This textbook emphasizes the interplay between algebra and geometry to motivate the study of advanced linear algebra techniques. Matrices and linear transformations are presented as two sides of the same coin, with their connection motivating inquiry throughout the book. Building on a first course in linear algebra, this book offers readers a deeper understanding of abstract structures, matrix decompositions, multilinearity, and tensors. Concepts draw on concrete examples throughout, offering accessible pathways to advanced techniques.

Beginning with a study of vector spaces that includes coordinates, isomorphisms, orthogonality, and projections, the book goes on to focus on matrix decompositions. Numerous decompositions are explored, including the Shur, spectral, singular value, and Jordan decompositions. In each case, the author ties the new technique back to familiar ones, to create a coherent set of tools. Tensors and multilinearity complete the book, with a study of the Kronecker product, multilinear transformations, and tensor products. Throughout, "Extra Topic" sections augment the core content with a wide range of ideas and applications, from the QR and Cholesky decompositions, to matrix-valued linear maps and semidefinite programming. Exercises of all levels accompany each section.

Advanced Linear and Matrix Algebra offers students of mathematics, data analysis, and beyond the essential tools and concepts needed for further study. The engaging color presentation and frequent marginal notes showcase the author's visual approach. A first course in proof-based linear algebra is assumed. An ideal preparation can be found in the author's companion volume, Introduction to Linear and Matrix Algebra.


lt;p> 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, Introduction to Linear and Matrix Algebra, is also published by Springer.

Chapter 1: Vector Spaces.- Chapter 2: Matrix Decompositions.- Chapter 3: Tensors and Multilinearity.- Appendix A: Mathematical Preliminaries.- Appendix B: Additional Proofs.- Appendix C: Selected Exercise Solutions.

"The book is well-organized. The main notions and results are well-presented, followed by a discussion and problems with detailed solutions. There are many helpful notes and examples. At the end of each section, the reader can frequently find several computational, true/false, or proof exercises. ... There are several illustrative and colorful figures. For instance, those illustrating the examples and remarks about the Gershgorin disc theorem or about the geometric interpretation of the positive semidefiniteness are really helpful." (Carlos M. da Fonseca, zbMATH 1471.15001, 2021)

“The book is well-organized. The main notions and results are well-presented, followed by a discussion and problems with detailed solutions. There are many helpful notes and examples. At the end of each section, the reader can frequently find several computational, true/false, or proof exercises. … There are several illustrative and colorful figures. For instance, those illustrating the examples and remarks about the Gershgorin disc theorem or about the geometric interpretation of the positive semidefiniteness are really helpful.” (Carlos M. da Fonseca, zbMATH 1471.15001, 2021)

Erscheinungsdatum
Zusatzinfo XVI, 494 p. 123 illus., 108 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 178 x 254 mm
Gewicht 964 g
Themenwelt Mathematik / Informatik Mathematik Algebra
Schlagworte Cholesky decomposition • Isomorphism linear algebra • jordan decomposition • Kronecker Product • linear algebra textbook • Linear transformation matrix • Matrix algebra textbook • Matrix algebra vs linear algebra • Matrix decomposition • Multilinearity • Multilinear transformations • Projections linear algebra • QR decomposition • Schur triangularization • Second course in linear algebra textbook • singular value decomposition • Spectral decomposition • Tensor products textbook • vector spaces
ISBN-10 3-030-52817-0 / 3030528170
ISBN-13 978-3-030-52817-1 / 9783030528171
Zustand Neuware
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