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Positive definite matrices

✍ Scribed by Rajendra Bhatia


Book ID
127454293
Publisher
Princeton University Press
Year
2007
Tongue
English
Weight
2 MB
Series
Princeton series in applied mathematics
Edition
illustrated edition
Category
Library
City
Princeton, N.J
ISBN
1400827787

No coin nor oath required. For personal study only.

✦ Synopsis


This book represents the first synthesis of the considerable body of new research into positive definite matrices. These matrices play the same role in noncommutative analysis as positive real numbers do in classical analysis. They have theoretical and computational uses across a broad spectrum of disciplines, including calculus, electrical engineering, statistics, physics, numerical analysis, quantum information theory, and geometry. Through detailed explanations and an authoritative and inspiring writing style, Rajendra Bhatia carefully develops general techniques that have wide applications in the study of such matrices.

Bhatia introduces several key topics in functional analysis, operator theory, harmonic analysis, and differential geometry--all built around the central theme of positive definite matrices. He discusses positive and completely positive linear maps, and presents major theorems with simple and direct proofs. He examines matrix means and their applications, and shows how to use positive definite functions to derive operator inequalities that he and others proved in recent years. He guides the reader through the differential geometry of the manifold of positive definite matrices, and explains recent work on the geometric mean of several matrices.

Positive Definite Matrices is an informative and useful reference book for mathematicians and other researchers and practitioners. The numerous exercises and notes at the end of each chapter also make it the ideal textbook for graduate-level courses.

✦ Subjects


Матрицы и определители


📜 SIMILAR VOLUMES


Positive Definite Matrices
✍ C. R. Johnson 📂 Article 📅 1970 🏛 Mathematical Association of America 🌐 English ⚖ 618 KB
Vector majorization via positive definit
✍ Richard A. Brualdi; Suk-Geun Hwang; Sung-Soo Pyo 📂 Article 📅 1997 🏛 Elsevier Science 🌐 English ⚖ 460 KB

It is well known that for real n-vectors y and x, y majorizes x if and only if Ay = x for some doubly stochastic matrix A of order n. If the components of each of y and x are in nonincreasing order, then it is known that the mat~x A can be chosen to be positive semidefinite symmetric. We characteriz

Determinantal inequalities for positive
✍ Charles R. Johnson; Wayne W. Barrett 📂 Article 📅 1993 🏛 Elsevier Science 🌐 English ⚖ 609 KB

We consider the problem of identifying all determinantal inequalities valid on all positive definite matrices. This is fundamentally a combinatorial problem about relations between collections of index sets. We describe some general structure of this problem and give sufficient and necessary conditi