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The third edition of this successful text describes and evaluates a range of widely used numerical methods, with an emphasis on problem solving. Every method is discussed thoroughly and illustrated with problems involving both hand computation and programming. MATLAB(R) M-files accompany each method and are available on the book's web page. Code is made simple and easy to understand by avoiding complex book-keeping schemes, while maintaining the essential features of the method. The third edition features a new chapter on Euler's method, a number of new and improved examples and exercises, and…mehr

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Produktbeschreibung
The third edition of this successful text describes and evaluates a range of widely used numerical methods, with an emphasis on problem solving. Every method is discussed thoroughly and illustrated with problems involving both hand computation and programming. MATLAB(R) M-files accompany each method and are available on the book's web page. Code is made simple and easy to understand by avoiding complex book-keeping schemes, while maintaining the essential features of the method. The third edition features a new chapter on Euler's method, a number of new and improved examples and exercises, and programs which appear as function M-files. Numerical Methods in Engineering with MATLAB(R), 3rd edition is a useful resource for both graduate students and practicing engineers.

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