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 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 G. Donald Allen - Texas A&M University
Contents: Vectors and Vector Spaces; Matrices and Linear Algebra; Eigenvalues and Eigenvectors; Unitary Matrices; Hermitian Theory; Normal Matrices; Factorization Theorems; Jordan Normal Form; Hermitian and Symmetric Matrices; Nonnegative Matrices.
by W. B. V. Kandasamy, F. Smarandache - InfoLearnQuest
This book is a continuation of the book n-linear algebra of type I. Most of the properties that could not be derived or defined for n-linear algebra of type I is made possible in this new structure which is introduced in this book.