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Difference Matrices for ODE and PDE - A MATLAB (R) Companion (Paperback, 1st ed. 2023)
Loot Price: R1,304
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Difference Matrices for ODE and PDE - A MATLAB (R) Companion (Paperback, 1st ed. 2023)
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The use of difference matrices and high-level MATLAB (R) commands
to implement finite difference algorithms is pedagogically novel.
This unique and concise textbook gives the reader easy access and a
general ability to use first and second difference matrices to set
up and solve linear and nonlinear systems in MATLAB which
approximate ordinary and partial differential equations.
Prerequisites include a knowledge of basic calculus, linear
algebra, and ordinary differential equations. Some knowledge of
partial differential equations is a plus though the text may easily
serve as a supplement for the student currently working through an
introductory PDEs course. Familiarity with MATLAB is not required
though a little prior experience with programming would be helpful.
In addition to its special focus on solving in MATLAB, the
abundance of examples and exercises make this text versatile in
use. It would serve well in a graduate course in introductory
scientific computing for partial differential equations. With
prerequisites mentioned above plus some elementary numerical
analysis, most of the material can be covered and many of the
exercises assigned in a single semester course. Some of the more
challenging exercises make substantial projects and relate to
topics from other typical graduate mathematics courses, e.g.,
linear algebra, differential equations, or topics in nonlinear
functional analysis. A selection of the exercises may be assigned
as projects throughout the semester. The student will develop the
skills to run simulations corresponding to the primarily
theoretical course material covered by the instructor. The book can
serve as a supplement for the instructor teaching any course in
differential equations. Many of the examples can be easily
implemented and the resulting simulation demonstrated by the
instructor. If the course has a numerical component, a few of the
more difficult exercises may be assigned as student projects.
Established researchers in theoretical partial differential
equations may find this book useful as well, particularly as an
introductory guide for their research students. Those unfamiliar
with MATLAB can use the material as a reference to quickly develop
their own applications in that language. Practical assistance in
implementing algorithms in MATLAB can be found in these pages. A
mathematician who is new to the practical implementation of methods
for scientific computation in general can learn how to implement
and execute numerical simulations of differential equations in
MATLAB with relative ease by working through a selection of
exercises. Additionally, the book can serve as a practical guide in
independent study, undergraduate or graduate research experiences,
or for reference in simulating solutions to specific thesis or
dissertation-related experiments.
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