This book is an extensively revised version of my textbook "¥esodot HaAlgebra HaLiniarit" (The Foundations of Linear Algebra) used at many universities in Israel. It is designed for a comprehensive one-year course in linear algebra (112 lecture hours) for mathematics majors. Therefore, I assume that the student already has a certain amount of mathematical background - including set theory, mathematical induction, basic analytic geometry, and elementary calculus - as wellas a modicum of mathematical sophistication. My intention is to provide not only a solid basis in the abstract theory of linear algebra, but also to provide examples of the application of this theory to other branches ofmathematics and computer science. Thus, for example, the introduction of finite fields is dictated by the needs of students studying algebraic coding theory as an immediate followup to their linear algebra studies. Many of the students studying linear algebra either are familiar with the care and feeding of computers before they begin their studies or are simultaneously en rolled in an introductory computer science course. Therefore, consideration of the more computational aspects of linear algebra - such as the solution of systems of linear equations and the calculation of eigenvalues - is delayed until all students are assumed able to write computer programs for this purpose. Beginning with Chap ter VII, there is an implicit assumption that the student has access to a personal computer and knows how to use it.

Klappentext
This volume presents a course in linear algebra for undergraduate mathematics students. It is considerably wider in its scope than most of the available methods and prepares the students for advanced work in algebra, differential equations, and functional analysis. Therefore, for example, it is transformation-oriented rather than matrix oriented, and whenever possible results are proved for arbitrary vector spaces and not merely for finite-dimensional vector spaces. Also, by proving results for vector spaces over arbitrary fields, rather than only the field of real or complex numbers, it prepares the way for the study of algebraic coding theory, automata theory, and other subjects in theoretical computer science. Topics are dealt with thoroughly, including ones that normally do not feature in undergraduate textbooks, and many novel and challenging exercises are given. The fact that most students are computer-literate is taken into account, not so much by emphasizing computational aspects of linear algebra which are best left to the computer, but by concentrating on the theory behind it. Audience: Recommended for a one-year undergraduate course in linear algebra.

Inhalt
Basic Notation and Terminology.- I. Fields and Integral Domains.- II. Vector Spaces.- III. Linear Independence and Dimension.- IV. Linear Transformations.- V. Endomorphism Rings of Vector Spaces.- VI. Representation of Linear Transformations by Matrices.- VII. Rings of Square Matrices.- VIII. Systems of Linear Equations.- IX. Determinants.- X. Eigenvectors and Eigenvalues.- XI. The Jordan Canonical Form.- XII. The Dual Space.- XIII. Inner Product Spaces.- XIV. Endomorphisms of Inner Product Spaces.- XV. The Moore-Penrose Pseudoinverse.- XVI. Bilinear transformations and forms.- XVII. Algebras over a field.