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 John Browne
The primary focus of this book is to provide a readable account in modern notation of Grassmann's major algebraic contributions to mathematics and science. It should be accessible to scientists and engineers, students and professionals alike.
by Peter J. Cameron - Queen Mary, University of London
On the theoretical side, we deal with vector spaces, linear maps, and bilinear forms. On the practical side, the subject is really about one thing: matrices. This module is a mixture of abstract theory and concrete calculations with matrices.