
Numerical Methods Using MATLAB, 3/e
John H. Mathews, California State University, Fullerton
Kurtis Fink, Northwest Missouri State University
Published December, 1998 by Prentice Hall Engineering/Science/Mathematics
Copyright 1999, 680 pp.
Cloth
ISBN 0132700425

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This text provides an introduction to numerical analysis
for either a single term course or a year long sequence.
It is suitable for undergraduate students in mathematics,
science, and engineering. Ample material is presented so that instructors
will be able to select topics appropriate to their needs.
NEW—Replaces all pseudocode algorithms with
MATLAB programs, taking advantage of MATLAB's widespread accessibility
for educational instruction.
 MATLAB's structured programming style is easy for students
to learn and resembles FORTRAN.
 MATLAB allows for simple modification and in the exercises,
students are encouraged to explore and compare modifications of algorithms.
 Builtin MATLAB commands facilitate the plotting of numerical
results from interpolation, curve fitting, differential equations,
etc., thereby developing an important graphical understanding of problems
and an invaluable sense of realism and enjoyment in numerical mathematics.
FEATURES
Provides a variety of examples and problems to develop and
sharpen students' skills in both the theory and practice of numerical
analysis.
 Includes easytoread proofs and workedout examples.
Presents a wealth of tables and graphs to illustrate computer
calculations in examples making the resulting numerical approximations
easier to interpret.
Emphasizes why numerical methods work and their limitations.
 Balances theory, error analysis, and readability.
 Presents an error analysis for each method with an approach
that is appropriate for the method at hand, but does not intimidate
students.
 Gives a mathematical derivation for each method that
uses elementary results and builds students' understanding of numerical
analysis.
Offers computer assignments implementing the algorithms
to give students an opportunity to practice their skills at scientific
programming.
Details algorithms in pseudocode.
Focuses on practical algorithms involving curve fitting,
function approximations, numerical integration, linear systems solution,
etc.
1. Preliminaries.
2. The Solution of Nonlinear Equations.
3. The Solution of Linear Systems.
4. Interpolation and Polynomial Approximation.
5. Curve Fitting.
6. Numerical Differentiation.
7. Numerical Integration.
8. Numerical Optimization.
9. Solution of Differential Equations.
10. Solution of Partial Differential Equations.
11. Eigenvalues and Eigenvectors.
Appendix: An Introduction to MATLAB.
Suggested References.
Bibliography and References.
Answers to Selected Exercises.
Index.
