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ACMES (Algorithms and Complexity in Mathematics, Epistemology, and
Science) is a multidisciplinary conference series that focuses on
epistemological and mathematical issues relating to computation in
modern science. This volume includes a selection of papers
presented at the 2015 and 2016 conferences held at Western
University that provide an interdisciplinary outlook on modern
applied mathematics that draws from theory and practice, and
situates it in proper context. These papers come from leading
mathematicians, computational scientists, and philosophers of
science, and cover a broad collection of mathematical and
philosophical topics, including numerical analysis and its
underlying philosophy, computer algebra, reliability and
uncertainty quantification, computation and complexity theory,
combinatorics, error analysis, perturbation theory, experimental
mathematics, scientific epistemology, and foundations of
mathematics. By bringing together contributions from researchers
who approach the mathematical sciences from different perspectives,
the volume will further readers' understanding of the multifaceted
role of mathematics in modern science, informed by the state of the
art in mathematics, scientific computing, and current modeling
techniques.
This book provides an extensive introduction to numerical computing
from the viewpoint of backward error analysis. The intended
audience includes students and researchers in science, engineering
and mathematics. The approach taken is somewhat informal owing to
the wide variety of backgrounds of the readers, but the central
ideas of backward error and sensitivity (conditioning) are
systematically emphasized. The book is divided into four parts:
Part I provides the background preliminaries including
floating-point arithmetic, polynomials and computer evaluation of
functions; Part II covers numerical linear algebra; Part III covers
interpolation, the FFT and quadrature; and Part IV covers numerical
solutions of differential equations including initial-value
problems, boundary-value problems, delay differential equations and
a brief chapter on partial differential equations. The book
contains detailed illustrations, chapter summaries and a variety of
exercises as well some Matlab codes provided online as
supplementary material. "I really like the focus on backward error
analysis and condition. This is novel in a textbook and a practical
approach that will bring welcome attention." Lawrence F. Shampine A
Graduate Introduction to Numerical Methods and Backward Error
Analysis" has been selected by Computing Reviews as a notable book
in computing in 2013. Computing Reviews Best of 2013 list consists
of book and article nominations from reviewers, CR category
editors, the editors-in-chief of journals, and others in the
computing community.
This book provides an extensive introduction to numerical computing
from the viewpoint of backward error analysis. The intended
audience includes students and researchers in science, engineering
and mathematics. The approach taken is somewhat informal owing to
the wide variety of backgrounds of the readers, but the central
ideas of backward error and sensitivity (conditioning) are
systematically emphasized. The book is divided into four parts:
Part I provides the background preliminaries including
floating-point arithmetic, polynomials and computer evaluation of
functions; Part II covers numerical linear algebra; Part III covers
interpolation, the FFT and quadrature; and Part IV covers numerical
solutions of differential equations including initial-value
problems, boundary-value problems, delay differential equations and
a brief chapter on partial differential equations. The book
contains detailed illustrations, chapter summaries and a variety of
exercises as well some Matlab codes provided online as
supplementary material. "I really like the focus on backward error
analysis and condition. This is novel in a textbook and a practical
approach that will bring welcome attention." Lawrence F. Shampine A
Graduate Introduction to Numerical Methods and Backward Error
Analysis" has been selected by Computing Reviews as a notable book
in computing in 2013. Computing Reviews Best of 2013 list consists
of book and article nominations from reviewers, CR category
editors, the editors-in-chief of journals, and others in the
computing community.
¿The best book on Maple just got better. This lively book is bursting with clear descriptions, revealing examples and top tips. It is gentle enough to act as an introduction and yet sufficiently comprehensive and well organised to serve as a reference manual. Maple Release 7 is significantly different to earlier releases, so this book will appeal even to hardened users who want to catch up fast.¿ ¿Des Higham, University of Strathclyde, UK This book provides an accelerated introduction to Maple for scientific programmers who already have experience in other computer languages (such as C, Pascal, or FORTRAN). It gives an overview of the most commonly used constructs and provides an elementary introduction to Maple programming. This edition of the book has been extensively updated for Maple Release 7 with future releases in mind. This has involved a substantial update of all programs, examples and exercises. Extensive new material has also been added, including an appendix on complex variables in a computer algebra context.
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Maple in Mathematics Education and Research - 4th Maple Conference, MC 2020, Waterloo, Ontario, Canada, November 2-6, 2020, Revised Selected Papers (Paperback, 1st ed. 2021)
Robert M. Corless, Jurgen Gerhard, Ilias S. Kotsireas
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R2,929
Discovery Miles 29 290
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Ships in 18 - 22 working days
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This book constitutes refereed proceedings of the 4th Maple
Conference, MC 2020, held in Waterloo, Ontario, Canada, in November
2020. The 25 revised full papers and 3 short papers were carefully
reviewed and selected out of 75 submissions, one invited paper is
also presented in the volume. The papers included in this book
cover topics in education, algorithms, and applciations of the
mathematical software Maple.
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