Description
Book SynopsisThe thoroughly revised and updated second edition of this acclaimed text for a second course on linear algebra has more than 1,100 problems and exercises, along with new sections on the singular value and CS decompositions and the Weyr canonical form, expanded treatments of inverse problems and of block matrices and much more.
Trade ReviewReview of the first edition: 'The presentation is straightforward and extremely readable. The authors' enthusiasm pervades the book, and the printing is what we expect from this publisher. This will doubtless be the standard text for years to come.' American Scientist
Review of the first edition: 'The reviewer strongly recommends that those working in either pure or applied linear algebra have this book on their desks.' SIAM Review
Review of the first edition: 'There seems little doubt that the book will become a standard reference for research workers in numerical mathematics.' Computing Reviews
Review of the first edition: '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.' Linear Algebra and its Applications
'The book is well organized, completely readable, and very enlightening. For researchers in matrix analysis, matrix computations, applied linear algebra, or computational science, this second edition is a valuable book.' Jesse L. Barlow, Computing Reviews
'With the additional material and exceedingly clear exposition, this book will remain the go-to book for graduate students and researchers alike in the area of linear algebra and matrix theory. I suspect there are few readers who will go through this book and not learn many new things. It is an invaluable reference for anyone working in this area.' Anne Greenbaum, SIAM Review
'The new edition is clearly a must-have for anyone seriously interested in matrix analysis.' Nick Higham, Applied Mathematics, Software and Workflow blog
Table of Contents1. Eigenvalues, eigenvectors, and similarity; 2. Unitary similarity and unitary equivalence; 3. Canonical forms for similarity, and triangular factorizations; 4. Hermitian matrices, symmetric matrices, and congruences; 5. Norms for vectors and matrices; 6. Location and perturbation of eigenvalues; 7. Positive definite and semi-definite matrices; 8. Positive and nonnegative matrices; Appendix A. Complex numbers; Appendix B. Convex sets and functions; Appendix C. The fundamental theorem of algebra; Appendix D. Continuous dependence of the zeroes of a polynomial on its coefficients; Appendix E. Continuity, compactness, and Weierstrass' theorem; Appendix F. Canonical pairs.
