Product Information
Ideal as a reference or quick review of the fundamentals of linear algebra, this book offers amatrix-oriented approach--with more emphasis on Euclidean n-space, problem solving, and applications, and less emphasis on abstract vector spaces. It features a variety of applications, boxed statements of important results, and a large number of numbered and unnumbered examples.Matrices, Vectors, and Systems of Linear Equations. Matrices and Linear Transformations. Determinants. Subspaces and Their Properties. Eigenvalues, Eigenvectors, and Diagonalization. Orthogonality. Vector Spaces. Complex Numbers.A professional reference for computer scientists, statisticians, and some engineers.Product Identifiers
PublisherPrentice Hall PTR
ISBN-100137167229
ISBN-139780137167227
eBay Product ID (ePID)628825
Product Key Features
Number of Pages451 Pages
Publication NameElementary Linear Algebra : a Matrix Approach
LanguageEnglish
SubjectAlgebra / Linear, Algebra / General
Publication Year1999
TypeTextbook
AuthorArnold J. Insel, Stephen H. Friedberg, Lawrence E. Spence
Subject AreaMathematics
Dimensions
Item Height0.9 in
Item Weight44.1 Oz
Item Length10.3 in
Item Width8.3 in
Additional Product Features
LCCN99-023843
Dewey Edition21
Target AudienceCollege Audience
IllustratedYes
Dewey Decimal512.5
Lc Classification NumberQa184.S68 2000
Table of Content1. Matrices, Vectors, and Systems of Linear Equations. Matrices and Vectors. Linear Combinations, Matrix-Vector Products, and Special Matrices. Systems of Linear Equations. Gaussian Elimination. Applications of Systems of Linear Equations. The Span of a Set Vectors. Linear Dependence and Independence. Chapter 1 Review. 2. Matrices and Linear Transformations. Matrix Multiplication. Applications of Matrix Multiplication. Invertibility and Elementary Matrices. The Inverse of a Matrix. The LU Decomposition of a Matrix. Linear Transformations and Matrices. Composition and Invertibility of Linear Transformations. Chapter 2 Review. 3. Determinants. Cofactor Expansion. Properties of Determinants. Chapter 3 Review. 4. Subspaces and Their Properties. Subspaces. Basis and Dimension. The Dimension of Subspaces Associated with a Matrix. Coordinate Systems. Matrix Representations of Linear Operators. Chapter 4 Review. 5. Eigenvalues, Eigenvectors, and Diagonalization. Eigenvalues and Eigenvectors. The Characteristic Polynomial. Diagonalization of Matrices. Diagonalization of Linear Operators. Applications of Eigenvalues. Chapter 5 Review. 6. Orthogonality. The Geometry of Vectors. Orthonormal Vectors. Least-Squares Approximation and Orthogonal Projection Matrices. Orthogonal Matrices and Operators. Symmetric Matrices. Singular Value Decomposition. Rotations of R3 and Computer Graphics. Chapter 6 Review. 7. Vector Spaces. Vector Spaces and their Subspaces. Dimension and Isomorphism. Linear Tranformations and Matrix Representations. Inner Product Spaces. Chapter 7 Review. Appendix: Complex Numbers.