Applied Linear Algebra and Matrix Analysis

Name: Applied Linear Algebra and Matrix Analysis
Price: 41.88 USD
Availability: InStock
ISBN: 9780387331959

ISBN-10: 0387331956

ISBN-13: 9780387331959

Edition: 2007

Authors: Thomas S. Shores

List price: $49.95

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Description:

This text is intended for a one or two semester sophomore level course in linear algebra. It is designed to provide a balance of applications, theory and computation, and to emphasize their interdependence. The text has a strong orientation towards numerical computation and the linear algebra needed in applied mathematics. At the same time, it contains a rigorous and self-contained development of most of the traditional topics in a linear algebra course. It provides background for numerous projects, which frequently require computational tools, but is not tied to any one computational platform. A comprehensive set of exercises and projects is included.

Book details

List price: $49.95
Copyright year: 2007
Publisher: Springer
Publication date: 8/14/2007
Binding: Paperback
Pages: 384
Size: 7.00" wide x 9.00" long x 1.00" tall
Weight: 1.386
Language: English




Linear Systems of Equations



Some Examples



Notation and a Review of Numbers



Gaussian Elimination: Basic Ideas



Gaussian Elimination: General Procedure



Computational Notes and Projects



Matrix Algebra



Matrix Addition and Scalar Multiplication



Matrix Multiplication



Applications of Matrix Arithmetic



Special Matrices and Transposes



Matrix Inverses



Basic Properties of Determinants



Computational Notes and Projects



Vector Spaces



Definitions and Basic Concepts



Subspaces



Linear Combinations



Subspaces Associated with Matrices and Operators



Bases and Dimension



Linear Systems Revisited



Computational Notes and Projects



Geometrical Aspects of Standard Spaces



Standard Norm and Inner Product



Applications of Norms and Inner Products



Orthogonal and Unitary Matrices



Change of Basis and Linear Operators



Computational Notes and Projects



The Eigenvalue Problem



Definitions and Basic Properties



Similarity and Diagonalization



Applications to Discrete Dynamical Systems



Orthogonal Diagonalization



Schur Form and Applications



The Singular Value Decomposition



Computational Notes and Projects



Geometrical Aspects of Abstract Spaces



Normed Spaces



Inner Product Spaces



Gram-Schmidt Algorithm



Linear Systems Revisited



Operator Norms



Computational Notes and Projects


Table of Symbols


Solutions to Selected Exercises


References


Index