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 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 William Thomson
Every important principle has been illustrated by copious examples, a considerable number of which have been fully worked out. As my main object has been to produce a textbook suitable for beginners, many important theorems have been omitted.
by W.B.V. Kandasamy, F. Smarandache, K. Ilanthenral - arXiv
This book introduced a new algebraic structure called linear bialgebra. We have ventured in this book to introduce new concepts like linear bialgebra and Smarandache neutrosophic linear bialgebra and also give the applications of these structures.
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.