Topics are introduced with goals, literature references and links to public software. There are descriptions of the current algorithms in LAPACK, GSLIB and MATLAB.
This book could be used for a second course in numerical methods, for either upper level undergraduates or first year graduate students. Parts of the text could be used for specialized courses, such as nonlinear optimization or iterative linear algebra.
Table of Contents
Chapter 1 Eigenvalues And Eigenvectors
Chapter 2 Iterative Linear Algebra
Chapter 3 Nonlinear Systems
Chapter 4 Constrained Optimization