Tobin A. Driscoll – författare

This book provides a comprehensive look at the Schwarz-Christoffel transformation, including its history and foundations, practical computation, common and less common variations, and many applications in fields such as electromagnetism, fluid flow, design and inverse problems, and the solution of linear systems of equations. It is an accessible resource for engineers, scientists, and applied mathematicians who seek more experience with theoretical or computational conformal mapping techniques. The most important theoretical results are stated and proved, but the emphasis throughout remains on concrete understanding and implementation, as evidenced by the 76 figures based on quantitatively correct illustrative examples. There are over 150 classical and modern reference works cited for readers needing more details. There is also a brief appendix illustrating the use of the Schwarz-Christoffel Toolbox for MATLAB, a package for computation of these maps.

This engaging book is a concise introduction to the essentials of the MATLAB programming language and is ideal for readers seeking a focused and brief approach to the software. Learning MATLAB contains numerous examples and exercises involving the software’s most useful and sophisticated features and an overview of the most common scientific computing tasks for which it can be used.The presentation is designed to guide new users through the basics of interacting with and programming in the MATLAB software, while also presenting some of its more important and advanced techniques, including how to solve common problem types in scientific computing. Rather than including exhaustive technical material, the author teaches through readily understood examples and numerous exercises that range from straightforward to very challenging. Readers are encouraged to learn by doing: entering the examples themselves, reading the online help, and trying the excercises.This engaging book is a concise introduction to the essentials of the MATLAB programming language.Learning MATLAB is ideal for readers seeking:A focused and brief approach to the software.Numerous examples and exercises involving the software’s most useful and sophisticated features.An overview of the most common scientific computing tasks for which the software can be used.

“If mathematical modeling is the process of turning real phenomena into mathematical abstractions, then numerical computation is largely about the transformation from abstract mathematics to concrete reality. Many science and engineering disciplines have long benefited from the tremendous value of the correspondence between quantitative information and mathematical manipulation.” -from the PrefaceFundamentals of Numerical Computation is an advanced undergraduate-level introduction to the mathematics and use of algorithms for the fundamental problems of numerical computation: linear algebra, finding roots, approximating data and functions, and solving differential equations. The book is organized with simpler methods in the first half and more advanced methods in the second half, allowing use for either a single course or a sequence of two courses. The authors take readers from basic to advanced methods, illustrating them with over 200 self-contained MATLAB functions and examples designed for those with no prior MATLAB experience. Although the text provides many examples, exercises, and illustrations, the aim of the authors is not to provide a cookbook per se, but rather an exploration of the principles of cooking.Professors Driscoll and Braun have developed an online resource that includes well-tested materials related to every chapter. Among these materials are lecture-related slides and videos, ideas for student projects, laboratory exercises, computational examples and scripts, and all the functions presented in the book.

Exploring ODEs is a textbook of ordinary differential equations for advanced undergraduates, graduate students, scientists, and engineers. It is unlike other books in this field in that each concept is illustrated numerically via a few lines of Chebfun code. There are about 400 computer-generated figures in all, and Appendix B presents 100 more examples as templates for further exploration.