This book is for students following an introductory course in numerical methods, numerical techniques or numerical analysis. It introduces MATLAB as a computing environment for experimenting with numerical methods. It approaches the subject from a pragmatic viewpoint; theory is kept at a minimum commensurate with comprehensive coverage of the subject and it contains abundant worked examples which provide easy understanding through a clear and concise theoretical treatment. This edition places even greater emphasis on 'learning by doing' than the previous edition.

Fully documented MATLAB code for the numerical methods described in the book will be available as supplementary material to to the book on http://extras.springer.com

Autorentext

Chris Woodford is a specialist adviser with the Newcastle University Computing Service. He is consulted by the staff and by students on matters relating to numerical, scientific and engineering computation. He gives Matlab courses and has used Matlab in developing multi-media applications. He has research interests and publications in the theory and application of the Finite Element method. Chris Woodford is also an Associate Lecturer with the Open University. He tutors a wide range of Maths and Computing courses and has been involved in the production of teaching material.

Chris Phillips is currently Dean of Undergraduate Studies in the Faculty of Science, Agriculture and Engineering at Newcastle University. He has taught extensively on courses involving numerical analysis and computer programming. He is an advocate of active learning and publishes pedagogic research papers in this area. His technical research has focussed on the numerical solution of integral and partial differential equations and parallel numerical algorithms.

Inhalt

1. Basic Matlab. - 2. Linear Equations.- 3. Nonlinear Equations.- 4. Curve Fitting.- 5. Numerical Integration.- 6. Numerical Differentiation.- 7. Linear Programming.- 8. Optimization.- 9. Ordinary Differential Equations.- 10. Eigenvalues and Eigenvectors.- 11. Statistics.