Based on courses taught to advanced undergraduate students, this book
offers a broad introduction to the methods of numerical linear algebra
and optimization. The prerequisites are familiarity with the basic
properties of matrices, finite-dimensional vector spaces and advanced
calculus, and some exposure to fundamental notions from functional
analysis. The book is divided into two parts. The first part deals with
numerical linear algebra (numerical analysis of matrices, direct and
indirect methods for solving linear systems, calculation of eigenvalues
and eigenvectors) and the second, optimizations (general algorithms,
linear and nonlinear programming). Summaries of basic mathematics are
provided, proof of theorems are complete yet kept as simple as possible,
applications from physics and mechanics are discussed, a great many
exercises are included, and there is a useful guide to further reading.