by Peter Petersen
Publisher: UCLA 2007
Number of pages: 300
This book covers the aspects of linear algebra that are included in most advanced undergraduate texts. All the usual topics from complex vectors spaces, complex inner products, The Spectral theorem for normal operators, dual spaces, quotient spaces, the minimal polynomial, the Jordan canonical form, and the rational canonical form are explained. A chapter on determinants has been included as the last chapter.
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by Yousef Saad - SIAM
This book discusses numerical methods for computing eigenvalues and eigenvectors of large sparse matrices. It provides an in-depth view of the numerical methods for solving matrix eigenvalue problems that arise in various engineering applications.
by Richard Barrett et al. - Society for Industrial Mathematics
The book focuses on the use of iterative methods for solving large sparse systems of linear equations. General and reusable templates are introduced to meet the needs of both the traditional user and the high-performance specialist.
by Zico Kolter - Stanford University
From the tabble of contents: Basic Concepts and Notation; Matrix Multiplication; Operations and Properties; Matrix Calculus (Gradients and Hessians of Quadratic and Linear Functions, Least Squares, Eigenvalues as Optimization, etc.).
by George Benthien
Tutorial describing many of the standard numerical methods used in Linear Algebra. Topics include Gaussian Elimination, LU and QR Factorizations, The Singular Value Decomposition, Eigenvalues and Eigenvectors via the QR Method, etc.