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 systems and numerical integrations. The presentation draws on geometrical intuition wherever appropriate and is supported by a large number of illustrations, exercises, and examples.
This work addresses the increasingly important role of numerical methods in science and engineering.
This is a textbook in numerical analysis and scientific computing intended for students with a year of calculus coursework, and familiarity with matrix algebra and differential equations.
It prepares graduate students for taking doctoral examinations in numerical analysis.The text covers the main areas o
The classroom-tested text helps students understand floating point number representations, particularly those pertaining to IEEE simple an
The text may also be used with other computing environments. This new edition offers a complete and thorough update. Parallel approaches, emerging hardware capabilities, computational modeling, and data science are given greater weight.
Taking an interdisciplinary approach, this new book provides a modern introduction to scientific computing, exploring numerical methods, computer technology, and their interconnections, which are treated with the goal of facilitating ...
Offers students a practical knowledge of modern techniques in scientific computing.
This new book from the authors of the classic book Numerical methods addresses the increasingly important role of numerical methods in science and engineering.
... 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.
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.