Handbook of Linear Algebra

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$135.95
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ISBN 9781584885108
Cat# C5106
 

Features

  • Presents basic as well as advanced linear algebra concepts, such as matrix perturbation theory and inverse eigenvalue problems
  • Features matrix notation throughout the text
  • Covers combinatorial and numerical linear algebra-two important branches of linear algebra
  • Explores both mathematical and nonmathematical applications, such as quantum computing, control theory, signal processing, and computational biology
  • Discusses software packages useful for linear algebra computations, including MATLAB®, Maple™, and Mathematica®
  • Provides numerous references for additional information along with a glossary that covers all major linear algebra terminology
  • Summary

    The Handbook of Linear Algebra provides comprehensive coverage of linear algebra concepts, applications, and computational software packages in an easy-to-use handbook format. The esteemed international contributors guide you from the very elementary aspects of the subject to the frontiers of current research.

    The book features an accessible layout of parts, chapters, and sections, with each section containing definition, fact, and example segments. The five main parts of the book encompass the fundamentals of linear algebra, combinatorial and numerical linear algebra, applications of linear algebra to various mathematical and nonmathematical disciplines, and software packages for linear algebra computations. Within each section, the facts (or theorems) are presented in a list format and include references for each fact to encourage further reading, while the examples illustrate both the definitions and the facts.

    Linearization often enables difficult problems to be estimated by more manageable linear ones, making the Handbook of Linear Algebra essential reading for professionals who deal with an assortment of mathematical problems.

    Table of Contents

    LINEAR ALGEBRA
    BASIC LINEAR ALGEBRA
    Vectors, Matrices and Systems of Linear Equations
    Linear Independence, Span, and Bases
    Linear Transformations
    Determinants and Eigenvalues
    Inner Product Spaces, Orthogonal Projection, Least Squares and Singular Value Decomposition

    MATRICES WITH SPECIAL PROPERTIES
    Canonical Forms
    Unitary Similarity, Normal Matrices and Spectral Theory
    Hermitian and Positive Definite Matrices
    Nonnegative and Stochastic Matrices
    Partitioned Matrices

    ADVANCED LINEAR ALGEBRA
    Functions of Matrices
    Quadratic, Bilinear and Sesquilinear Forms
    Multilinear Algebra
    Matrix Equalities and Inequalities
    Matrix Perturbation Theory
    Pseudospectra
    Singular Values and Singular Value Inequalities
    Numerical Range
    Matrix Stability and Inertia

    TOPICS IN ADVANCED LINEAR ALGEBRA
    Inverse Eigenvalue Problems
    Totally Positive and Totally Nonnegative Matrices
    Linear Preserver Problems
    Matrices over Integral Domains
    Similarity of Families of Matrices
    Max-Plus Algebra
    Matrices Leaving a Cone Invariant

    COMBINATORIAL MATRIX THEORY AND GRAPHS
    MATRICES AND GRAPHS
    Combinatorial Matrix Theory
    Matrices and Graphs
    Digraphs and Matrices
    Bipartite Graphs and Matrices

    TOPICS IN COMBINATORIAL MATRIX THEORY
    Permanents
    D-Optimal Designs
    Sign Pattern Matrices
    Multiplicity Lists for the Eigenvalues of Symmetric Matrices with a Given Graph
    Matrix Completion Problems
    Algebraic Connectivity

    NUMERICAL METHODS
    NUMERICAL METHODS FOR LINEAR SYSTEMS
    Vector and Matrix Norms, Error Analysis, Efficiency and Stability
    Matrix Factorizations and Direct Solution of Linear Systems
    Least Squares Solution of Linear Systems
    Sparse Matrix Methods
    Iterative Solution Methods for Linear Systems

    NUMERICAL METHODS FOR EIGENVALUES
    Symmetric Matrix Eigenvalue Techniques
    Unsymmetric Matrix Eigenvalue Techniques
    The Implicitly Restarted Arnoldi Method
    Computation of the Singular Value Decomposition
    Computing Eigenvalues and Singular Values to High Relative Accuracy

    COMPUTATIONAL LINEAR ALGEBRA
    Fast Matrix Multiplication
    Structured Matrix Computations
    Large-Scale Matrix Computations

    APPLICATIONS
    APPLICATIONS TO OPTIMIZATION
    Linear Programming
    Semidefinite Programming

    APPLICATIONS TO PROBABILITY AND STATISTICS
    Random Vectors and Linear Statistical Models
    Multivariate Statistical Analysis
    Markov Chains

    APPLICATIONS TO ANALYSIS
    Differential Equations and Stability
    Dynamical Systems and Linear Algebra
    Control Theory
    Fourier Analysis

    APPLICATIONS TO PHYSICAL AND BIOLOGICAL SCIENCES
    Linear Algebra and Mathematical Physics
    Linear Algebra in Biomolecular Modeling

    APPLICATIONS TO COMPUTER SCIENCE
    Coding Theory
    Quantum Computation
    Information Retrieval and Web Search
    Signal Processing

    APPLICATIONS TO GEOMETRY
    Geometry
    Some Applications of Matrices and Graphs in Euclidean Geometry

    APPLICATIONS TO ALGEBRA
    Matrix Groups
    Group Representations
    Nonassociative Algebras
    Lie Algebras

    COMPUTATIONAL SOFTWARE
    INTERACTIVE SOFTWARE FOR LINEAR ALGEBRA
    MATLAB
    Linear Algebra in Maple
    Mathematica

    PACKAGES OF SUBROUTINES FOR LINEAR ALGEBRA
    BLAS
    LAPACK
    Use of ARPACK and EIGS
    Summary of Software for Linear Algebra Freely Available on the Web

    GLOSSARY
    NOTATION INDEX
    INDEX

    Editorial Reviews

    "…a valuable compendium of information on virtually all aspects of linear algebra and its applications. …This is a Herculean labor of love on the editor's part, a successful effort that should be appreciated and applauded by anyone working and/or teaching in this important area of mathematics. … Every library that supports mathematics and science departments should have this encyclopedic work on its shelves."
    -Henry Ricardo, MAA Reviews, June 2007

    "Without doubts, it will be of great help for everybody, who needs Linear Algebra in his profession, or for instructors or students looking for concepts, results, or examples."

    – H. Mitsch, in Monatshefte fur Math, 2007, Vol. 151, No. 3

    "This handbook covers all the major topics of linear algebra at both graduate and undergraduate level, as well as their applications and related software packages.  The handbook will be without a doubt a valuable resource for anyone using linear algebra, i.e. basically for any mathematician."                                                                                          - EMS Newsletter

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