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Contains a unified exposition of spectral variation inequalities for matrices. The text provides a complete and self-contained collection of bounds for the distance between the eigenvalues of two matrices, which could be arbitrary or restricted to specific classes. Many basic results and techniques can be found in this book, making it a good reference for researchers and students.For the SIAM Classics edition, the author has added a new Supplements section, which includes recent results and discusses the important advances made in the study of theory, results, and proof techniques of spectral variation problems in the two decades since the book’s original publication.
Rajendra Bhatia is a Professor in the Department of Statistics and Mathematics at the Indian Statistical Institute.
Preface to the Classics EditionPrefaceIntroductionChapter1: PreliminariesChapter 2: Singular values and normsChapter 3: Spectral variation of Hermitian matricesChapter 4: Spectral variation of normal matricesChapter 5: The general spectral variation problemChapter 6: Arbitrary perturbations of constrained matricesPostscriptsReferencesSupplements 1986–2006Chapter 7: Singular values and normsChapter 8: Spectral variation of Hermitian matricesChapter 9: Spectral variation of normal matricesChapter 10: Spectral variation of diagonalizable matricesChapter 11: The general spectral variation problemChapter 12: Arbitrary perturbations of constrained matricesChapter 13: Related TopicsBibliographyErrata.