Numerical Methods

The fourth edition of Numerical Methods Using MATLAB® provides a clear and rigorous introduction to a wide range of numerical methods that have practical applications. The authors' approach is to integrate MATLAB® with numerical analysis in a way which adds clarity to the numerical analysis and develops familiarity with MATLAB®. MATLAB® 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® to help researchers analyze a particular outcome. By using MATLAB® 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.

• Features many numerical algorithms, their fundamental principles, and applications
• Includes new sections introducing Simulink, Kalman Filter, Discrete Transforms and Wavelet Analysis
• Contains some new problems and examples
• Is user-friendly and is written in a conversational and approachable style
• Contains over 60 algorithms implemented as MATLAB® functions, and over 100 MATLAB® scripts applying numerical algorithms to specific examples

Autorentext

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

Inhalt

1. An Introduction to Matlab 2. Linear Equations and Eigensystems 3. Solution of Nonlinear Equations 4. Differentiation and Integration 5. Solution of Differential Equations 6. Boundary Value Problems 7. Analyzing Data 8. Analyzing Data using Discrete Transforms 9. Optimization Methods 10. Applications of the Symbolic Toolbox