Numerical Methods in Engineering with MATLAB / Edition 2

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Overview

Numerical Methods in Engineering with MATLAB® is a text for engineering students and a reference for practicing engineers. The choice of numerical methods was based on their relevance to engineering problems. Every method is discussed thoroughly and illustrated with problems involving both hand computation and programming. MATLAB M-files accompany each method and are available on the book website. This code is made simple and easy to understand by avoiding complex book-keeping schemes, while maintaining the essential features of the method. MATLAB was chosen as the example language because of its ubiquitous use in engineering studies and practice. This new edition includes the new MATLAB anonymous functions, which allow the programmer to embed functions into the program rather than storing them as separate files. Other changes include the addition of rational function interpolation in Chapter 3, the addition of Ridder’s method in place of Brent’s method in Chapter 4, and the addition of downhill simplex method in place of the Fletcher-Reeves method of optimization in Chapter 10.
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Editorial Reviews

From the Publisher
'Highly recommended.' The Times Higher Education Supplement
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Product Details

  • ISBN-13: 9780521191333
  • Publisher: Cambridge University Press
  • Publication date: 9/30/2009
  • Edition description: New Edition
  • Edition number: 2
  • Pages: 448
  • Product dimensions: 7.70 (w) x 9.80 (h) x 1.20 (d)

Meet the Author

Jaan Kiusalaas is a Professor Emeritus in the Department of Engineering Science and Mechanics at the Pennsylvania State University. He has taught numerical methods, including finite element and boundary element methods, for more than 30 years. He is also the co-author of four other books - Engineering Mechanics: Statics, Engineering Mechanics: Dynamics, Mechanics of Materials and an alternate version of this work with Python code.
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Table of Contents

1. Introduction to MATLAB®; 2. Systems of linear algebraic equations; 3. Interpolation and curve fitting; 4. Roots of equations; 5. Numerical differentiation; 6. Numerical integration; 7. Initial value problems; 8. Two-point boundary value problems; 9. Symmetric matrix eigenvalue problems; 10. Introduction to optimization; Appendices.
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