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 Leif Mejlbro - BookBoon
The book is a collection of solved problems in linear algebra. The second volume covers geometrical vectors, vector spaces and linear maps. All examples are solved, and the solutions usually consist of step-by-step instructions.
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.
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 W. B. V. Kandasamy, F. Smarandache - InfoLearnQuest
n-Linear Algebra of type I introduced in this book finds applications in Markov chains and Leontief economic models. Scientists and engineers can adopt this concept in fuzzy finite element analysis of mechanical structures with uncertain parameters.