Numerical Linear Algebra and Applications / Edition 2

by Biswa Nath Datta

Overview

Full of features and applications, this acclaimed textbook for upper undergraduate level and graduate level students includes all the major topics of computational linear algebra, including solution of a system of linear equations, least-squares solutions of linear systems, computation of eigenvalues, eigenvectors, and singular value problems. Drawing from numerous disciplines of science and engineering, the author covers a variety of motivating applications. When a physical problem is posed, the scientific and engineering significance of the solution is clearly stated. Each chapter contains a summary of the important concepts developed in that chapter, suggestions for further reading, and numerous exercises, both theoretical and MATLAB® and MATCOM based. The author also provides a list of key words for quick reference. The MATLAB toolkit available online, ‘MATCOM', contains implementations of the major algorithms in the book and will enable students to study different algorithms for the same problem, comparing efficiency, stability, and accuracy.

Product Details

ISBN-13:	9780898716856
Publisher:	SIAM
Publication date:	02/04/2010
Edition description:	New Edition
Pages:	554
Product dimensions:	6.85(w) x 9.72(h) x 1.18(d)

About the Author

Biswa Nath Datta is Professor of Mathematical Sciences, Adjunct Professor of Electrical and Mechanical Engineering, and Distinguished Research Professor at Northern Illinois University. He has authored more than 115 interdisciplinary research papers, the books Numerical Methods for Linear Control Systems Design and Analysis and Numerical Linear Algebra and Applications, and several associated software packages. He was elected a Fellow of IEEE in 2000, inducted an Academician of the Academy of Nonlinear Sciences in 2002, and named a recipient of a Senior Fulbright Specialist award, an IEEE Distinguished Lecturer award, and several IEEE Plaques of Honor.

Table of Contents

Preface; 1. Linear algebra problems, their importance, and computational difficulties; 2. A review of some required concepts from core linear algebra; 3. Floating point numbers and errors in computations; 4. Stability of algorithms and conditioning of problems; 5. Gaussian elimination and LU factorization; 6. Numerical solutions of linear systems; 7. QR factorization, singular value decomposition, and projections; 8. Least-squares solutions to linear systems; 9. Numerical matrix eigenvalue problems; 10. Numerical symmetric eigenvalue problem and singular value decomposition; 11. Generalized and quadratic eigenvalue problems; 12. Iterative methods for large and sparse problems: an overview; 13. Key terms in numerical linear algebra; Bibliography; Index; Online materials; 14. Special topics; Appendix A. Some software for matrix computations; Appendix B. A brief introduction to MATLAB®; Appendix C. MATCOM and selected MATCOM commands; Appendix D. Partial solutions and answers to selected problems.