Softcover ISBN: | 978-1-4704-7419-5 |
Product Code: | GSM/232.S |
List Price: | $89.00 |
MAA Member Price: | $80.10 |
AMS Member Price: | $71.20 |
eBook ISBN: | 978-1-4704-7418-8 |
Product Code: | GSM/232.E |
List Price: | $85.00 |
MAA Member Price: | $76.50 |
AMS Member Price: | $68.00 |
Softcover ISBN: | 978-1-4704-7419-5 |
eBook: ISBN: | 978-1-4704-7418-8 |
Product Code: | GSM/232.S.B |
List Price: | $174.00 $131.50 |
MAA Member Price: | $156.60 $118.35 |
AMS Member Price: | $139.20 $105.20 |
Softcover ISBN: | 978-1-4704-7419-5 |
Product Code: | GSM/232.S |
List Price: | $89.00 |
MAA Member Price: | $80.10 |
AMS Member Price: | $71.20 |
eBook ISBN: | 978-1-4704-7418-8 |
Product Code: | GSM/232.E |
List Price: | $85.00 |
MAA Member Price: | $76.50 |
AMS Member Price: | $68.00 |
Softcover ISBN: | 978-1-4704-7419-5 |
eBook ISBN: | 978-1-4704-7418-8 |
Product Code: | GSM/232.S.B |
List Price: | $174.00 $131.50 |
MAA Member Price: | $156.60 $118.35 |
AMS Member Price: | $139.20 $105.20 |
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Book DetailsGraduate Studies in MathematicsVolume: 232; 2023; 485 ppMSC: Primary 15; 30; 34; 39; 46; 47; 52; 93
This is a Revised Edition of: GSM/78.R
This book is based largely on courses that the author taught at the Feinberg Graduate School of the Weizmann Institute. It conveys in a user-friendly way the basic and advanced techniques of linear algebra from the point of view of a working analyst. The techniques are illustrated by a wide sample of applications and examples that are chosen to highlight the tools of the trade. In short, this is material that the author has found to be useful in his own research and wishes that he had been exposed to as a graduate student.
Roughly the first quarter of the book reviews the contents of a basic course in linear algebra, plus a little. The remaining chapters treat singular value decompositions, convexity, special classes of matrices, projections, assorted algorithms, and a number of applications. The applications are drawn from vector calculus, numerical analysis, control theory, complex analysis, convex optimization, and functional analysis. In particular, fixed point theorems, extremal problems, best approximations, matrix equations, zero location and eigenvalue location problems, matrices with nonnegative entries, and reproducing kernels are discussed.
This new edition differs significantly from the second edition in both content and style. It includes a number of topics that did not appear in the earlier edition and excludes some that did. Moreover, most of the material that has been adapted from the earlier edition has been extensively rewritten and reorganized.
ReadershipUndergraduate and graduate students and researchers interested in learning and teaching linear algebra with an emphasis on concrete algorithms.
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Table of Contents
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Chapters
-
Prerequisites
-
Dimension and rank
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Gaussian elimination
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Eigenvalues and eigenvectors
-
Towards the Jordan decomposition
-
The Jordan decomposition
-
Determinants
-
Companion matrices and circulants
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Inequalities
-
Normed linear spaces
-
Inner product spaces
-
Orthogonality
-
Normal matrices
-
Projections, volumes, and traces
-
Singular value decomposition
-
Positive definite and semidefinite matrices
-
Determinants redux
-
Applications
-
Discrete dynamical systems
-
Continuous dynamical systems
-
Vector-valued functions
-
Fixed point theorems
-
The implicit function theorem
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Extremal problems
-
Newton’s method
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Matrices with nonnegative entries
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Applications of matrices with nonnegative entries
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Eigenvalues of Hermitian matrices
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Singular values redux I
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Singular values redux II
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Approximation by unitary matrices
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Linear functionals
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A minimal norm problem
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Conjugate gradients
-
Continuity of eigenvalues
-
Eigenvalue location problems
-
Matrix equations
-
A matrix completion problem
-
Minimal norm completions
-
The numerical range
-
Riccati equations
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Supplementary topics
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Toeplitz, Hankel, and de Branges
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-
Additional Material
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RequestsReview Copy – for publishers of book reviewsDesk Copy – for instructors who have adopted an AMS textbook for a courseExamination Copy – for faculty considering an AMS textbook for a courseAccessibility – to request an alternate format of an AMS title
- Book Details
- Table of Contents
- Additional Material
- Requests
This is a Revised Edition of: GSM/78.R
This book is based largely on courses that the author taught at the Feinberg Graduate School of the Weizmann Institute. It conveys in a user-friendly way the basic and advanced techniques of linear algebra from the point of view of a working analyst. The techniques are illustrated by a wide sample of applications and examples that are chosen to highlight the tools of the trade. In short, this is material that the author has found to be useful in his own research and wishes that he had been exposed to as a graduate student.
Roughly the first quarter of the book reviews the contents of a basic course in linear algebra, plus a little. The remaining chapters treat singular value decompositions, convexity, special classes of matrices, projections, assorted algorithms, and a number of applications. The applications are drawn from vector calculus, numerical analysis, control theory, complex analysis, convex optimization, and functional analysis. In particular, fixed point theorems, extremal problems, best approximations, matrix equations, zero location and eigenvalue location problems, matrices with nonnegative entries, and reproducing kernels are discussed.
This new edition differs significantly from the second edition in both content and style. It includes a number of topics that did not appear in the earlier edition and excludes some that did. Moreover, most of the material that has been adapted from the earlier edition has been extensively rewritten and reorganized.
Undergraduate and graduate students and researchers interested in learning and teaching linear algebra with an emphasis on concrete algorithms.
-
Chapters
-
Prerequisites
-
Dimension and rank
-
Gaussian elimination
-
Eigenvalues and eigenvectors
-
Towards the Jordan decomposition
-
The Jordan decomposition
-
Determinants
-
Companion matrices and circulants
-
Inequalities
-
Normed linear spaces
-
Inner product spaces
-
Orthogonality
-
Normal matrices
-
Projections, volumes, and traces
-
Singular value decomposition
-
Positive definite and semidefinite matrices
-
Determinants redux
-
Applications
-
Discrete dynamical systems
-
Continuous dynamical systems
-
Vector-valued functions
-
Fixed point theorems
-
The implicit function theorem
-
Extremal problems
-
Newton’s method
-
Matrices with nonnegative entries
-
Applications of matrices with nonnegative entries
-
Eigenvalues of Hermitian matrices
-
Singular values redux I
-
Singular values redux II
-
Approximation by unitary matrices
-
Linear functionals
-
A minimal norm problem
-
Conjugate gradients
-
Continuity of eigenvalues
-
Eigenvalue location problems
-
Matrix equations
-
A matrix completion problem
-
Minimal norm completions
-
The numerical range
-
Riccati equations
-
Supplementary topics
-
Toeplitz, Hankel, and de Branges