Designed for a one-semester course, Introduction to Numerical Analysis and Scientific Computing presents fundamental concepts of numerical mathematics and explains how to implement and program numerical methods. The classroom-tested text helps students understand floating point number representations, particularly those pertaining to IEEE simple an
This work addresses the increasingly important role of numerical methods in science and engineering.
This book introduces the main topics of modern numerical analysis: sequence of linear equations, error analysis, least squares, nonlinear systems, symmetric eigenvalue problems, three-term recursions, interpolation and approximation, large ...
A book that emphasizes the importance of solving differential equations on a computer, which comprises a large part of what has come to be called scientific computing.
This textbook is a comprehensive introduction to computational mathematics and scientific computing suitable for undergraduate and postgraduate courses.
Praise for the First Edition ". . . outstandingly appealing with regard to its style, contents, considerations of requirements of practice, choice of examples, and exercises." —Zentrablatt Math ". . . carefully structured with many ...
The codes used for most of the computational examples in the text are available on GitHub. This new edition includes material necessary for an upper division course in computational linear algebra.
Stroud, A. H., and D. Secrest. 1966. Gaussian Quadrature Formulas. ... Todd, J. 1961. Computational problems concerning the Hilbert matrix. JR-NBS 65, 19–22. Todd, M. J. 1982. An introduction to piecewise linear homotopy 766 ...
... A. Greenbaum, S. Hammarling, A. McKenney, and D. Sorensen. LAPACK Users' Guide. SIAM, Philadelphia, 3d edition, 1999. S. L. Anderson. Random number generators on vector supercomputers and other advanced architectures.
This book is an introduction to numerical methods for solving linear and nonlinear systems of equations as well as ordinary and partial differential equations, and for approximating curves, functions, and integrals.
To make the book as practical as possible, the authors explore their subject both from a theoretical, mathematical perspective and from an implementation-driven, programming perspective.