Numerical Methods for Large Eigenvalue Problems
by Yousef Saad
Publisher: SIAM 2011
Number of pages: 285
This book discusses numerical methods for computing eigenvalues and eigenvectors of large sparse matrices. It provides an in-depth view of the numerical methods that are applicable for solving matrix eigenvalue problems that arise in various engineering and scientific applications.
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by Vasilios N. Katsikis - InTech
Topics: Matrices, Moments and Quadrature; Structured Approaches to General Inverse Eigenvalue Problems; Eigenvalue Problems; Nonnegative Inverse Elementary Divisors Problem; Some Recent Advances in Nonlinear Inverse Scattering in 2D; and more.
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.
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 W.B.V. Kandasamy, F. Smarandache, K. Ilanthenral - arXiv
This book introduced a new algebraic structure called linear bialgebra. We have ventured in this book to introduce new concepts like linear bialgebra and Smarandache neutrosophic linear bialgebra and also give the applications of these structures.