by Jonathan Gleason
Publisher: University of California 2018
Number of pages: 681
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.
Home page url
Download or read it online for free here:
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 George Benthien
Tutorial describing many of the standard numerical methods used in Linear Algebra. Topics include Gaussian Elimination, LU and QR Factorizations, The Singular Value Decomposition, Eigenvalues and Eigenvectors via the QR Method, etc.
by Ray M. Bowen, C.-C.Wang - Springer
This book presents the basics of vector and tensor analysis for science and engineering students. Volume 1 covers algebraic structures and a modern introduction to the algebra of vectors and tensors. Clear presentation of mathematical concepts.
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.