Preface; Review and miscellanea; 1. Eigenvalues, eigenvectors, and similarity; 2. Unitary equivalence and normal matrices; 3. Canonical forms; 4. Hermitian and symmetric matrices; 5. Norms for vectors and matrices; 6. Location and perturbation of eigenvalues; 7. Positive definite matrices; 8. Non-negative matrices; 9. Appendices; References.
Matrix Analysis presents the classical and recent results for matrix analysis that have proved to be important to applied mathematics.
'There seems little doubt that the book will become a standard reference for research workers in numerical mathematics.' Computing Reviews 'The reviewer strongly recommends that those working in either pure or applied linear algebra have this book on their desks.' SIAM Review 'This will doubtless be the standard text for years to come.' American Scientists 'On the whole the authors have done an excellent job of supplying linear algebraists and applied mathematicians with a well-organized comprehensive survey, which can serve both as a text and as a reference. The reviewer recommends that everyone working in these fields have this book on his/her desk.' Linear Algebra and its Applications
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