| Titre : |
Applied linear algebra |
| Type de document : |
texte imprimé |
| Auteurs : |
BEN NOBLE, Auteur ; James W. DANIEL, Auteur |
| Editeur : |
Prentice-hall |
| Année de publication : |
1988 |
| Importance : |
521 p. |
| Format : |
25 cm. |
| ISBN/ISSN/EAN : |
978-0-13-041260-7 |
| Note générale : |
Index |
| Langues : |
Anglais (eng) |
| Catégories : |
MATHÉMATIQUES:Algébre
|
| Index. décimale : |
04-03 Algébre |
| Résumé : |
Contains important modern applications such as signal processing and Karmarkar's approach to linear programming. Uses Gauss reduction and 'Gauss-reduced form' as the fundamental theoretical and computational tool. Includes examples and problems using modern software for matrix computations, and describes properties and sources of software for real applied problems. Stresses both the theoretical and practical importance of tools such as the singular-value decomposition and generalized (pseudo) inverses, the QR decomposition, Householder transformations/matrices, and orthogonal projections. Features 1,100 exercises, including optional computer examples and problems.
SOMMAIRE:
MATRIX ALGEBRA
SOME SIMPLE APPLICATIONS AND QUESTION
SOLVING EQUATIONS AND FINDING INVERSES: METHODS
SOLVING EQUATIONS AND FINDING INVERSES: THEORY
VECTORS AND VECTOR SPACES
LINEAR TRANSFORMATIONS AND MATRICES
EIGENVALUES AND EIGENVECTORS: AN OVERVIEW
EIGENSYSTEMS OF SYMMETRIC, AND NORMAL MATRICES, WITH APPLICATIONS
EIGNSYSTEMS OF GENERAL MATRICES, WITH APPLICATIONS
QUADRATIC FORMS AND VARIATIONAL CHARACTERIZATIONS OF EIGENVALUES
LINEAR PROGRAMMING
ANSWERS AND AIDS TO SELECTED PROBLEMS |
Applied linear algebra [texte imprimé] / BEN NOBLE, Auteur ; James W. DANIEL, Auteur . - Prentice-hall, 1988 . - 521 p. ; 25 cm. ISBN : 978-0-13-041260-7 Index Langues : Anglais ( eng)
| Catégories : |
MATHÉMATIQUES:Algébre
|
| Index. décimale : |
04-03 Algébre |
| Résumé : |
Contains important modern applications such as signal processing and Karmarkar's approach to linear programming. Uses Gauss reduction and 'Gauss-reduced form' as the fundamental theoretical and computational tool. Includes examples and problems using modern software for matrix computations, and describes properties and sources of software for real applied problems. Stresses both the theoretical and practical importance of tools such as the singular-value decomposition and generalized (pseudo) inverses, the QR decomposition, Householder transformations/matrices, and orthogonal projections. Features 1,100 exercises, including optional computer examples and problems.
SOMMAIRE:
MATRIX ALGEBRA
SOME SIMPLE APPLICATIONS AND QUESTION
SOLVING EQUATIONS AND FINDING INVERSES: METHODS
SOLVING EQUATIONS AND FINDING INVERSES: THEORY
VECTORS AND VECTOR SPACES
LINEAR TRANSFORMATIONS AND MATRICES
EIGENVALUES AND EIGENVECTORS: AN OVERVIEW
EIGENSYSTEMS OF SYMMETRIC, AND NORMAL MATRICES, WITH APPLICATIONS
EIGNSYSTEMS OF GENERAL MATRICES, WITH APPLICATIONS
QUADRATIC FORMS AND VARIATIONAL CHARACTERIZATIONS OF EIGENVALUES
LINEAR PROGRAMMING
ANSWERS AND AIDS TO SELECTED PROBLEMS |
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