Matrix Analysis and Algorithms
by Andrew Stuart, Jochen Voss
Publisher: CaltechAUTHORS 2009
Number of pages: 108
The book contains an introduction to matrix analysis, and to the basic algorithms of numerical linear algebra. Contents: Vector and Matrix Analysis; Matrix Factorisations; Stability and Conditioning; Complexity of Algorithms; Systems of Linear Equations; Iterative Methods; Least Squares Problems; Eigenvalue Problems.
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by Kaare Brandt Petersen, Michael Syskind Pedersen
The Matrix Cookbook is a free desktop reference on matrix identities, inequalities, approximations and relations useful for different fields such as machine learning, statistics, quantum mechanics, engeneering, chemistry.
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Random matrix theory is at the intersection of linear algebra, probability theory and integrable systems, and has a wide range of applications. The book contains articles on random matrix theory such as integrability and free probability theory.
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