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Numerical Methods: Using MATLAB

Autor George Lindfield, John Penny
en Limba Engleză Paperback – sep 2025
The fifth edition of Numerical Methods Using MATLAB® continues to provide 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
  • 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
  • Availailable ancillaries include a solutions manual and image bank for instructors, and for all users, downloadable versions of all MATLAB file scripts and functions listed in the text
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Specificații

ISBN-13: 9780443264986
ISBN-10: 0443264988
Pagini: 640
Dimensiuni: 191 x 235 mm
Ediția:5
Editura: ELSEVIER SCIENCE

Cuprins

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