Applied Numerical Methods Using MATLAB, 2nd edition
Won Y. Yang, Chung-Ang University;
Wenwu Cao, Pennsylvania State University;
Jaekwon Kim, Yonsei University;
Kyung W. Park, Yonsei University;
Ho-Hyun Park, Chung-Ang University;
Jingon Joung, Chung-Ang University;
Jong-Suk Ro, Seoul National University;
Han L. Lee, Chung-Ang University;
Cheol-Ho Hong, Chung-Ang University;
Taeho Im, Hoseo University
John Wiley & Sons, Inc., 2020
ISBN: 978-1-119-62680-0;
Language: English
Applied Numerical Methods Using MATLAB, 2nd edition uses MATLAB to teach the fundamental concepts for applying numerical methods to solve practical engineering and science problems. It presents programs in a complete form so that readers can run them instantly with no programming skill, allowing them to focus on understanding the mathematical manipulation process and making interpretations of the results.
The book begins with an introduction to MATLAB usage and computational errors, covering everything from input/output of data, to various kinds of computing errors, and on to parameter sharing and passing, and more. The system of linear equations is covered next, followed by a chapter on the interpolation by Lagrange polynomial. The next sections look at interpolation and curve fitting, nonlinear equations, numerical differentiation/integration, ordinary differential equations, and optimization. Numerous methods such as the Simpson, Euler, Heun, Runge-kutta, Golden Search, Nelder-Mead, and more are all covered in those chapters. The eighth chapter provides readers with matrices and Eigenvalues and Eigenvectors. The book finishes with a complete overview of differential equations.
Key Features
- Provides examples and problems of solving electronic circuits and neural networks
- Includes new sections on adaptive filters, recursive least-squares estimation, Bairstow's method for a polynomial equation, and more
- Explains Mixed Integer Linear Programing (MILP) and DOA (Direction of Arrival) estimation with eigenvectors
- Aimed at students who do not like and/or do not have time to derive and prove mathematical results
MATLAB is introduced in an appendix and is used throughout the book to solve example problems. The authors also briefly discuss Partial Differential Equation Toolbox and Symbolic Math Toolbox and use them to solve relevant examples. The MATLAB code used in the book is also available for download.
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