Computational Partial Differential Equations Using MATLAB (Textbooks in Mathematics)

Li, Jichun; Chen, Yi-Tung

ISBN 10: 1420089048 / ISBN 13: 9781420089042

Published by Chapman and Hall/CRC (edition 1), 2008

About this Item

CD or DVD included. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Seller Inventory # 1420089048-11-1-15

Bibliographic Details

• Title: Computational Partial Differential Equations Using MATLAB (Textbooks in Mathematics)
• Publisher: Chapman and Hall/CRC (edition 1)
• Publication Date: 2008
• Language: English
• ISBN 10: 1420089048
• ISBN 13: 9781420089042
• Binding: Hardcover
• Edition: 1.
• Condition: Very Good

About this title

Synopsis

This textbook introduces several major numerical methods for solving various partial differential equations (PDEs) in science and engineering, including elliptic, parabolic, and hyperbolic equations. It covers traditional techniques that include the classic finite difference method and the finite element method as well as state-of-the-art numerical methods, such as the high-order compact difference method and the radial basis function meshless method.

Helps Students Better Understand Numerical Methods through Use of MATLAB^®
The authors uniquely emphasize both theoretical numerical analysis and practical implementation of the algorithms in MATLAB, making the book useful for students in computational science and engineering. They provide students with simple, clear implementations instead of sophisticated usages of MATLAB functions.

All the Material Needed for a Numerical Analysis Course
Based on the authors’ own courses, the text only requires some knowledge of computer programming, advanced calculus, and difference equations. It includes practical examples, exercises, references, and problems, along with a solutions manual for qualifying instructors. Students can download MATLAB code from www.crcpress.com, enabling them to easily modify or improve the codes to solve their own problems.

About the Author

University of California at Los Angeles, USA University of Nevada, Las Vegas, USA