Applied and Computational Linear Algebra: A First Course
by Charles L. Byrne
Publisher: University of Massachusetts Lowell 2013
Number of pages: 504
This book is intended as 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. Often the particular nature of the applications will prompt us to seek algorithms with particular properties; we then turn to the matrix theory to understand the workings of the algorithms.
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by Zico Kolter - Stanford University
From the tabble of contents: Basic Concepts and Notation; Matrix Multiplication; Operations and Properties; Matrix Calculus (Gradients and Hessians of Quadratic and Linear Functions, Least Squares, Eigenvalues as Optimization, etc.).
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 John Browne
The primary focus of this book is to provide a readable account in modern notation of Grassmann's major algebraic contributions to mathematics and science. It should be accessible to scientists and engineers, students and professionals alike.
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.