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Applied Linear Algebra and Matrix Analysis

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Linear Systems of Equationsp. 1
Some Examplesp. 1
Notation and a Review of Numbersp. 9
Gaussian Elimination: Basic Ideasp. 21
Gaussian Elimination: General Procedurep. 33
Computational Notes and Projectsp. 46
Matrix Algebrap. 55
Matrix Addition and Scalar Multiplicationp. 55
Matrix Multiplicationp. 62
Applications of Matrix Arithmeticp. 71
Special Matrices and Transposesp. 86
Matrix Inversesp. 101
Basic Properties of Determinantsp. 114
Computational Notes and Projectsp. 129
Vector Spacesp. 145
Definitions and Basic Conceptsp. 145
Subspacesp. 161
Linear Combinationsp. 170
Subspaces Associated with Matrices and Operatorsp. 183
Bases and Dimensionp. 191
Linear Systems Revisitedp. 198
Computational Notes and Projectsp. 208
Geometrical Aspects of Standard Spacesp. 211
Standard Norm and Inner Productp. 211
Applications of Norms and Inner Productsp. 221
Orthogonal and Unitary Matricesp. 233
Change of Basis and Linear Operatorsp. 242
Computational Notes and Projectsp. 247
The Eigenvalue Problemp. 251
Definitions and Basic Propertiesp. 251
Similarity and Diagonalizationp. 263
Applications to Discrete Dynamical Systemsp. 272
Orthogonal Diagonalizationp. 282
Schur Form and Applicationsp. 287
The Singular Value Decompositionp. 291
Computational Notes and Projectsp. 294
Geometrical Aspects of Abstract Spacesp. 305
Normed Spacesp. 305
Inner Product Spacesp. 312
Gram-Schmidt Algorithmp. 323
Linear Systems Revisitedp. 333
Operator Normsp. 342
Computational Notes and Projectsp. 348
Table of Symbolsp. 355
Solutions to Selected Exercisesp. 357
Referencesp. 375
Indexp. 377
Table of Contents provided by Ingram. All Rights Reserved.

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This new book offers a fresh approach to matrix and linear algebra by providing a balanced blend of applications, theory, and computation, while highlighting their interdependence. Intended for a one-semester course, Applied Linear Algebra and Matrix Analysis places special emphasis on linear algebra as an experimental science, with numerous examples, computer exercises, and projects. While the flavor is heavily computational and experimental, the text is independent of specific hardware or software platforms. Throughout the book, significant motivating examples are woven into the text, and each section ends with a set of exercises. The student will develop a solid foundation in the following topics *Gaussian elimination and other operations with matrices *basic properties of matrix and determinant algebra *standard Euclidean spaces, both real and complex *geometrical aspects of vectors, such as norm, dot product, and angle *eigenvalues, eigenvectors, and discrete dynamical systems *general norm and inner-product concepts for abstract vector spaces For many students, the tools of matrix and linear algebra will be as fundamental in their professional work as the tools of calculus; thus it is important to ensure that students appreciate the utility and beauty of these subjects as well as the mechanics. By including applied mathematics and mathematical modeling, this new textbook will teach students how concepts of matrix and linear algebra make concrete problems workable. Thomas S. Shores is Professor of Mathematics at the University of Nebraska, Lincoln, where he has received awards for his teaching. His research touches on group theory, commutative algebra, mathematical modeling, numerical analysis, and inverse theory.

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