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Advanced Linear Algebra

A Concise Text with Contemporary Applications

Häftad, Engelska, 2025

679 kr

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The second edition of this engaging textbook for advanced undergraduate students and beginning graduates covers all the core subjects in linear algebra. It has a unique emphasis on integrating ideas from analysis, in addition to pure algebra, and features a balance of abstraction, practicality, and contemporary applications. Four chapters examine some of the most important of these applications, including quantum mechanics, machine learning, data science, and quantum information. The material is supplemented by a rich collection of exercises designed for students from diverse backgrounds, including a wealth of newly added ones in this edition. Selected solutions are provided at the back of the book for use in self-study, and full solutions are available online to instructors.

Produktinformation

Utgivningsdatum2025-06-12
Mått151 x 229 x 26 mm
Vikt690 g
FormatHäftad
SpråkEngelska
Antal sidor472
Upplaga2
FörlagCambridge University Press
ISBN9781009589840

Tillhör följande kategorier

Notation and convention; 1. Vector spaces; 2. Linear mappings; 3. Determinants; 4. Scalar products; 5. Real quadratic forms and self-adjoint mappings; 6. Complex quadratic forms and self-adjoint mappings; 7. Jordan decomposition; 8. Selected topics; 9. Excursion: Quantum mechanics in a nutshell; 10. Excursion: Problems in machine learning; 11. Excursion: Problems in data analysis; 12. Excursion: Multilinear algebra; 13. Excursion: Essentials of quantum information and quantum entanglement; Solutions to selected problems; Bibliographic notes; Bibliography; Index.

'Mastering the intricacies of linear algebra has never been easier. This textbook offers a clear, engaging approach that demystifies complex concepts while providing some contemporary applications in quantum mechanics, machine learning, and data science. A valuable resource for both students and professionals eager to deepen their understanding of this foundational discipline!' Jichun Li, University of Nevada, Las Vegas