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 Charles L. Byrne - University of Massachusetts Lowell
This book is a text for a graduate course that focuses on applications of linear algebra and on the algorithms used to solve the problems that arise in those applications. Tthe particular nature of the applications will prompt us to seek algorithms.
by Jonathan Gleason - University of California
From the table of contents: K-modules and linear transformations; Linear independence, spanning, bases, and dimension; Coordinates, column vectors, and matrices; Eigenstuff; Multilinear algebra and tensors; Inner-product spaces; Applications.
by M. Duits, A.B.J. Kuijlaars, M. Yue Mo - American Mathematical Society
The authors consider the two matrix model with an even quartic potential and an even polynomial potential. The main result is the formulation of a vector equilibrium problem for the limiting mean density for the eigenvalues of one of the matrices.
by Simon J.A. Malham - Heriot-Watt University
From the table of contents: Linear second order ODEs; Homogeneous linear ODEs; Non-homogeneous linear ODEs; Laplace transforms; Linear algebraic equations; Matrix Equations; Linear algebraic eigenvalue problems; Systems of differential equations.