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 W. B. V. Kandasamy, F. Smarandache - InfoQuest
In this book, the authors introduce the notion of Super linear algebra and super vector spaces using the definition of super matrices defined by Horst (1963). This book expects the readers to be well-versed in linear algebra.
by James V. Herod - Georgia Tech
These notes are about linear operators on Hilbert Spaces. The text is an attempt to provide a way to understand the ideas without the students already having the mathematical maturity that a good undergraduate analysis course could provide.
by Leif Mejlbro - BookBoon
The book is a collection of solved problems in linear equations, matrices and determinants. All examples are solved, and the solutions consist of step-by-step instructions, and are designed to assist students in methodically solving problems.
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.).