Numerical Methods: Using MATLAB / Edition 4

by George Lindfield, John Penny

Overview

The fourth edition of Numerical Methods Using MATLAB(R) provides a clear and rigorous introduction to a wide range of numerical methods that have practical applications. The authors' approach is to integrate MATLAB(R) with numerical analysis in a way which adds clarity to the numerical analysis and develops familiarity with MATLAB(R). MATLAB(R) graphics and numerical output are used extensively to clarify complex problems and give a deeper understanding of their nature.

The text provides an extensive reference providing numerous useful and important numerical algorithms that are implemented in MATLAB(R) to help researchers analyze a particular outcome. By using MATLAB(R) it is possible for the readers to tackle some large and difficult problems and deepen and consolidate their understanding of problem solving using numerical methods. Many worked examples are given together with exercises and solutions to illustrate how numerical methods can be used to study problems that have applications in the biosciences, chaos, optimization and many other fields. The text will be a valuable aid to people working in a wide range of fields, such as engineering, science and economics.

Product Details

ISBN-13:	9780128122563
Publisher:	Elsevier Science
Publication date:	10/16/2018
Edition description:	4th ed.
Pages:	608
Product dimensions:	7.40(w) x 9.10(h) x 1.20(d)

About the Author

George Lindfield is a former lecturer in Mathematics and Computing at the School of Engineering and Applied Science, Aston University in the United Kingdom.

John Penny is an Emeritus Professor of Mechanical Engineering at the School of Engineering and Applied Science, Aston University in the United Kingdom.

Table of Contents

1. An Introduction to Matlab
2. Linear Equations and Eigensystems
3. Solution of Nonlinear Equations
4. Differentiation and Integration
5. Ordinary Differential Equations
6. Partial Differential Equations
7. Interpolation and Least Squares Approximation
8. Analyzing Data using Discrete Transforms
9. Optimization Methods
10. Machine Learning
11. Applications of the Symbolic Toolbox

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From the Publisher

Provides clear, authoritative coverage of an extensive range of numerical methods that have practical applications in engineering and scientific problems