This book is
meant to provide an introduction to vectors, matrices, and least squares
methods, basic topics in applied linear algebra. Our goal is to give the
beginning student, with little or no prior exposure to linear algebra, a good
grounding in the basic ideas, as well as an appreciation for how they are used
in many applications, including data fitting, machine learning and artificial
intelligence, tomography, image processing, finance, and automatic control
systems. Topics covered includes: Vectors, Norm and distance, Clustering,
Matrices, Linear equations, Matrix multiplication, Linear dynamical systems,
Least squares, Multi-objective least squares, Constrained least squares.
The purpose with
these notes is to introduce students to the concept of proof in linear algebra
in a gentle manner. Topics covered includes: Matrices and Matrix Operations,
Linear Equations, Vector Spaces, Linear Transformations, Determinants, Eigenvalues and Eigenvectors, Linear Algebra and Geometry.
This is a book on
linear algebra and matrix theory. It provides an introduction to various
numerical methods used in linear algebra. This is done because of the
interesting nature of these methods. Topics covered includes: Matrices And
Linear Transformations, Determinant, Row Operations, Factorizations, Vector
Spaces And Fields, Linear Transformations, Inner Product Spaces, Norms For
Finite Dimensional Vector Spaces.
This textbook is suitable for a
sophomore level linear algebra course taught in about twenty-five lectures. It
is designed both for engineering and science majors, but has enough abstraction
to be useful for potential math majors. Our goal in writing it was to produce
students who can perform computations with linear systems and also understand
the concepts behind these computations.
Author(s): David Cherney,
Tom Denton, Rohit Thomas and Andrew Waldron
This collection of
exercises is designed to provide a framework for discussion in a junior level
linear algebra class conducted fairly regularly at Portland State University.
Topics covered includes: Matrices And Linear Equations, Vector Spaces , Linear
Maps Between Vector Spaces , Spectral Theory Of Vector Spaces, The Geometry Of
Inner Product Spaces , Adjoint Operators, Spectral Theory Of Inner Product
This book is not a ”traditional” book in the sense that it does not include
any applications to the material discussed. Its aim is solely to learn the basic
theory of linear algebra within a semester period. Topics covered includes: Linear Systems, Matrices,
Determinants, The Theory of Vector Spaces, Eigenvalues and Diagonalization and