This self-contained textbook presents matrix analysis in the context of numerical computation with numerical conditioning of problems and numerical stability of algorithms at the forefront. Using a unique combination of numerical insight and mathematical rigor, it advances readers understanding of two phenomena: sensitivity of linear systems and least squares problems, and numerical stability of algorithms.&Nbsp; this book differs from other numerical linear algebra texts by offering

A systematic development of numerical conditioning,
A simplified concept of numerical stability in exact Arithmetic,
simple derivations,

A high-level view of algorithms, and results for complex matrices.
The material is presented at a basic level, emphasizing ideas and intuition, and each Chapter offers simple exercises for use in the classroom and more challenging exercises for student practice.
This book is intended for first-year graduate students in Engineering, operations research, computational Science, and all areas of Mathematics. It also is appropriate for self-study.