Ebook: A Concise Introduction to Linear Algebra
Author: Géza Schay (auth.)
- Tags: Linear and Multilinear Algebras Matrix Theory, General Algebraic Systems, Mathematical Physics, Mathematical Methods in Physics, Theoretical Mathematical and Computational Physics
- Year: 2012
- Publisher: Birkhäuser Basel
- City: New York
- Edition: 1
- Language: English
- pdf
Building on the author's previous edition on the subject (Introduction toLinear Algebra, Jones & Bartlett, 1996), this book offers a refreshingly concise text suitable for a standard course in linear algebra, presenting a carefully selected array of essential topics that can be thoroughly covered in a single semester. Although the exposition generally falls in line with the material recommended by the Linear Algebra Curriculum Study Group, it notably deviates in providing an early emphasis on the geometric foundations of linear algebra. This gives students a more intuitive understanding of the subject and enables an easier grasp of more abstract concepts covered later in the course.
The focus throughout is rooted in the mathematical fundamentals, but the text also investigates a number of interesting applications, including a section on computer graphics, a chapter on numerical methods, and many exercises and examples using MATLAB. Meanwhile, many visuals and problems (a complete solutions manual is available to instructors) are included to enhance and reinforce understanding throughout the book.
Brief yet precise and rigorous, this work is an ideal choice for a one-semester course in linear algebra targeted primarily at math or physics majors. It is a valuable tool for any professor who teaches the subject.
Analytic Geometry of Euclidean Spaces -- Systems of Linear Equations, Matrices -- Vector Spaces and Subspaces -- Linear Transformations -- Orthogonal Projections and Bases -- Determinants -- Eigenvalues and Eigenvectors -- Numerical Methods
Analytic Geometry of Euclidean Spaces -- Systems of Linear Equations, Matrices -- Vector Spaces and Subspaces -- Linear Transformations -- Orthogonal Projections and Bases -- Determinants -- Eigenvalues and Eigenvectors -- Numerical Methods