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.
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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 G. Donald Allen - Texas A&M University
Contents: Vectors and Vector Spaces; Matrices and Linear Algebra; Eigenvalues and Eigenvectors; Unitary Matrices; Hermitian Theory; Normal Matrices; Factorization Theorems; Jordan Normal Form; Hermitian and Symmetric Matrices; Nonnegative Matrices.
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 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.