622 Pages 9 B/W Illustrations
    by Chapman & Hall

    Advanced Linear Algebra, Second Edition takes a gentle approach that starts with familiar concepts and then gradually builds to deeper results. Each section begins with an outline of previously introduced concepts and results necessary for mastering the new material. By reviewing what students need to know before moving forward, the text builds a solid foundation upon which to progress.

    The new edition of this successful text focuses on vector spaces and the maps between them that preserve their structure (linear transformations). Designed for advanced undergraduate and beginning graduate students, the book discusses the structure theory of an operator, various topics on inner product spaces, and the trace and determinant functions of a linear operator. It addresses bilinear forms with a full treatment of symplectic spaces and orthogonal spaces, as well as explains the construction of tensor, symmetric, and exterior algebras.

    Featuring updates and revisions throughout, Advanced Linear Algebra, Second Edition:

    • Contains new chapters covering sesquilinear forms, linear groups and groups of isometries, matrices, and three important applications of linear algebra
    • Adds sections on normed vector spaces, orthogonal spaces over perfect fields of characteristic two, and Clifford algebras
    • Includes several new exercises and examples, with a solutions manual available upon qualifying course adoption

    The book shows students the beauty of linear algebra while preparing them for further study in mathematics.

    Preface to the Second Edition

    Preface to the First Edition

    Acknowledgments

    List of Figures

    Symbol Description

    Vector Spaces

    Fields

    The Space ₣n

    Vector Spaces over an Arbitrary Field

    Subspaces of Vector Spaces

    Span and Independence

    Bases and Finite-Dimensional Vector Spaces

    Bases and Infinite-Dimensional Vector Spaces

    Coordinate Vectors

    Linear Transformations

    Introduction to Linear Transformations

    The Range and Kernel of a Linear Transformation

    The Correspondence and Isomorphism Theorems

    Matrix of a Linear Transformation

    The Algebra of (V,W) and Mmn(₣)

    Invertible Transformations and Matrices

    Polynomials

    The Algebra of Polynomials

    Roots of Polynomials

    Theory of a Single Linear Operator

    Invariant Subspaces of an Operator

    Cyclic Operators

    Maximal Vectors

    Indecomposable Linear Operators

    Invariant Factors and Elementary Divisors

    Canonical Forms

    Operators on Real and Complex Vector Spaces

    Normed and Inner Product Spaces

    Inner Products

    Geometry in Inner Product Spaces

    Orthonormal Sets and the Gram-Schmidt Process

    Orthogonal Complements and Projections

    Dual Spaces

    Adjoints

    Normed Vector Spaces

    Linear Operators on Inner Product Spaces

    Self-Adjoint and Normal Operators

    Spectral Theorems

    Normal Operators on Real Inner Product Spaces

    Unitary and Orthogonal Operators

    The Polar Decomposition and Singular Value Decomposition

    Trace and Determinant of a Linear Operator

    Trace of a Linear Operator

    Determinant of a Linear Operator and Matrix

    Uniqueness of the Determinant of a Linear Operator

    Bilinear Forms

    Basic Properties of Bilinear Maps

    Symplectic Spaces

    Quadratic Forms and Orthogonal Space

    Orthogonal Space, Characteristic Two

    Real Quadratic Forms

    Sesquilinear Forms and Unitary Geometry

    Basic Properties of Sesquilinear Forms

    Unitary Space

    Tensor Products

    Introduction to Tensor Products

    Properties of Tensor Products

    The Tensor Algebra

    The Symmetric Algebra

    The Exterior Algebra

    Clifford Algebras, char ₣ ≠ 2

    Linear Groups and Groups of Isometries

    Linear Groups

    Symplectic Groups

    Orthogonal Groups, char ₣ ≠ 2

    Unitary Groups

    Additional Topics in Linear Algebra

    Matrix Norms

    The Moore–Penrose Inverse of a Matrix

    Nonnegative Matrices

    The Location of Eigenvalues

    Functions of Matrices

    Applications of Linear Algebra

    Least Squares

    Error Correcting Codes

    Ranking Webpages for Search Engines

    Appendices

    Concepts from Topology and Analysis

    Concepts from Group Theory

    Answers to Selected Exercises

    Hints to Selected Problems

    Bibliography

    Index

    Biography

    Bruce Cooperstein is a professor of mathematics at the University of California, Santa Cruz, USA. He was a visiting scholar at the Carnegie Foundation for the Advancement of Teaching (spring 2007) and a recipient of the Kellogg National Fellowship (1982–1985) and the Pew National Fellowship for Carnegie Scholars (1999–2000). Dr. Cooperstein has authored numerous papers in refereed mathematics journals.

    "This is the substantially extended second edition of a book comprising an advanced course in linear algebra …"
    Zentralblatt MATH 1319

    Praise for the First Edition:
    "The book is well written, and the examples are appropriate. … Each section contains relevant problems at the end. The ‘What You Need to Know’ feature at the beginning of each section outlining the knowledge required to grasp the material is useful. Summing Up: Recommended."
    CHOICE, January 2011

    "Pedagogically, a structural and general approach is taken, and topically, the material has been chosen in order to cover the material a beginning graduate student would be expected to know when taking a first course in group or field theory or functional analysis."
    SciTech Book News, February 2011