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Hardcover Numerical Methods for Partial Differential Equations Book

ISBN: 0120567601

ISBN13: 9780120567607

Numerical Methods for Partial Differential Equations

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Format: Hardcover

Condition: Good*

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Book Overview

This volume is designed as an introduction to the concepts of modern numerical analysis as they apply to partial differential equations. The book contains many practical problems and their solutions, but at the same time, strives to expose the pitfalls--such as overstability, consistency requirements, and the danger of extrapolation to nonlinear problems methods used on linear problems. Numerical Methods for Partial Differential Equations, Third Edition reflects the great accomplishments that have taken place in scientific computation in the fifteen years since the Second Edition was published. This new edition is a drastic revision of the previous one, with new material on boundary elements, spectral methods, the methods of lines, and invariant methods. At the same time, the new edition retains the self-contained nature of the older version, and shares the clarity of its exposition and the integrity of its presentation. Key Features * Material on finite elements and finite differences have been merged, and now constitute equal partners * Additional material has been added on boundary elements, spectral methods, the method of lines, and invariant methods * References have been updated, and reflect the additional material * Self-contained nature of the Second Edition has been maintained * Very suitable for PDE courses

Related Subjects

Math Mathematics Science & Math

Customer Reviews

1 rating

Very good and helpful book for the engineer with fundamental

This book is very detail on how to generate numerical methods for partial differential equations. Staring from basics, the author proceeds with detailed examples and more complicated ideas. This is book will be very helpful for the people having basic computational knowledge and scientific computing experience. But the book is written in 1977. Some difficult ideas will be easier to be implemented on large scale computers such as Linux clusters or SGI machines. I also found one small shortcoming is that the problem complexity is not detailed discussed. This will be very important now for comparing different algorithms to accomplish the same problem.
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