Author Description

<p><b>This new edition provides an updated approach for students, engineers, and researchers to apply numerical methods for solving problems using MATLAB</b>^&reg;&nbsp;</p> <p>This accessible book makes use of MATLAB^&reg; software to teach the fundamental concepts for applying numerical methods to solve practical engineering and/or 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.</p> <p><i>Applied Numerical Methods Using MATLAB^&reg;, Second Edition</i> 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.</p> <ul> <li>Provides examples and problems of solving electronic circuits and neural networks</li> <li>Includes new sections on adaptive filters, recursive least-squares estimation, Bairstow's method for a polynomial equation, and more</li> <li>Explains Mixed Integer Linear Programing (MILP) and DOA (Direction of Arrival) estimation with eigenvectors</li> <li>Aimed at students who do not like and/or do not have time to derive and prove mathematical results</li> </ul> <p><i>Applied Numerical Methods Using MATLAB<sup>&r