Random Matrix Theory, Interacting Particle Systems and Integrable Systems
by Percy Deift, Peter Forrester (eds)
Publisher: Cambridge University Press 2014
Number of pages: 528
Random matrix theory is at the intersection of linear algebra, probability theory and integrable systems, and has a wide range of applications in physics, engineering, multivariate statistics and beyond. The book contains review articles and research contributions on all these topics, in addition to other core aspects of random matrix theory such as integrability and free probability theory.
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by Autar K Kaw - University of South Florida
This book is written primarily for students who are at freshman level or do not take a full course in Linear/Matrix Algebra, or wanting a contemporary and applied approach to Matrix Algebra. Eight chapters of the book are available for free.
by Shmuel Friedland - University of Illinois at Chicago
From the table of contents: Domains, Modules and Matrices; Canonical Forms for Similarity; Functions of Matrices and Analytic Similarity; Inner product spaces; Elements of Multilinear Algebra; Nonnegative matrices; Convexity.
by Marco Taboga - StatLect
This is a collection of 98 short and self-contained lectures on the most important topics in linear algebra. There are hundreds of examples, solved exercises and detailed derivations. The step-by-step approach makes the book easy to understand.
by Steven J Cox - Rice University
Matrix theory is a language for representing and analyzing multivariable systems. These notes will demonstrate the role of matrices in the modeling of physical systems and the power of matrix theory in the analysis and synthesis of such systems.