After reading this book, students should be able to analyze
computational problems in linear algebra such as linear systems, least
squares- and eigenvalue problems, and to develop their own algorithms
for solving them.
Since these problems can be large and difficult to handle, much can be
gained by understanding and taking advantage of special structures. This
in turn requires a good grasp of basic numerical linear algebra and
matrix factorizations. Factoring a matrix into a product of simpler
matrices is a crucial tool in numerical linear algebra, because it
allows us to tackle complex problems by solving a sequence of easier
ones.
The main characteristics of this book are as follows:
It is self-contained, only assuming that readers have completed
first-year calculus and an introductory course on linear algebra, and
that they have some experience with solving mathematical problems on a
computer. The book provides detailed proofs of virtually all results.
Further, its respective parts can be used independently, making it
suitable for self-study.
The book consists of 15 chapters, divided into five thematically
oriented parts. The chapters are designed for a one-week-per-chapter,
one-semester course. To facilitate self-study, an introductory chapter
includes a brief review of linear algebra.