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D�tails bibliographiques

Titre : Numerical Methods: Using MATLAB

�diteur : Academic Press

Date d'�dition : 2012

Reliure : paperback

Etat : Good

Edition : 3�me �dition

A propos de ce titre

Synopsis :

Numerical Methods Offering useful and important numerical algorithms that can be implemented into MATLAB for a graphical interpretation to help researchers analyze a particular outcome, this title contains over 500 numerical algorithms, their fundamental principles, and applications. Full description

Quatri�me de couverture:

Skillfully balancing rigor with practicality, this progressive and visually rich piece on using MATLAB software explores how this modern and powerful computing technology can—in an elegant and efficient way—solve exacting and interesting problems that have application in science and industry. Encouraging systematic experimentation, it offers an extensive, hands-on study of MATLAB functions and exposes the reader to a wide range of numerical algorithms—including optimization and regression analysis with applications of symbolic methods—with full explanations of their fundamental principles and illustrations of their application.

FEATURES/BENEFITS

Developing computing technology used through all algorithms and scripts.
Clear visual interpretation of results using MATLAB graphics.
Use of symbolic methods—Includes a full chapter on the use of the MATLAB symbolic toolbox and its application to numerical methods.
- Allows comparison of different approaches to many problems and enhances opportunities for testing and experimentation.
Introduction to the important field of optimization.
- Helps the reader understand the broad area of MATLAB application.
Statistical techniques placed in a clear numerical context.
- Enables the reader to grasp complex but widely applied concepts.
MATLAB symbolic toolbox—Includes a full chapter on the use of the MATLAB symbolic toolbox and its applications to numerical methods.
The most current MATLAB functions—Includes functions for obtaining specific eigenvalues; for the solution of differential equations (including methods for stiff differential equations); and for regression analysis.
Coverage on global optimization methods.