Introduction to Applied Linear Algebra by Stephen Boyd and Lieven Vandenberghe
File Type :PDF Number of Pages :473
Description 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, Multiobjective least squares, Constrained least squares.
