Linear Algebra - Vector and Inner Product Spaces

This book is a comprehensive guide to Linear Algebra and covers all the fundamental topics such as vector spaces, linear independence, basis, linear transformations, matrices, determinants, inner products, eigenvectors, bilinear forms, and canonical forms. It also introduces concepts such as fields, rings, group homomorphism, and binary operations early on, which gives students a solid foundation to understand the rest of the material.
Unlike other books on Linear Algebra that are either too theory-oriented with fewer solved examples or too problem-oriented with less good quality theory, this book strikes a balance between the two. It provides easy-to-follow theorem proofs and a considerable number of worked examples with various levels of difficulty. The fundamentals of the subject are explained in a methodical and straightforward way.
This book is aimed at undergraduate and graduate students of Mathematics and Engineering Mathematics who are studying Linear Algebra. It is also a useful resource for students preparing for exams in higher education competitions such as NET, GATE, lectureships, etc. The book includes some of the most recent and challenging questions from these exams.

Dettagli sul prodotto

• Autori: Saurabh Chandra Maury
• Editore: De Gruyter
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 02.12.2024
• EAN: 9783111515700
• ISBN: 978-3-11-151570-0
• Pagine: 264
• Peso: 466 g
• Serie: de Gruyter Textbook
• Categorie: Scienze naturali, medicina, informatica, tecnica > Matematica; Elektrotechnik, Algebra, Geometrie, Computerprogrammierung und Softwareentwicklung, Textbook, computer science, Electrical Engineering, geometry, Applied mathematics, Electronics engineering, Computer Programming / Software Development, TEC007000 Technology & Engineering / Electrical, Vector spaces, COM014000 COMPUTERS / Computer Science, MAT003000 MATHEMATICS / Applied, Linear Transformations, Diagonalization of Matrices, MAT012030 MATHEMATICS / Geometry / Differential, Determinants and Eigenvalues, Inner Product Spaces