Authors:
- Presents recent original research in numerical analysis and fractional calculus
- Provides self-contained chapters, each with an extensive list of references
- Presents Newton-like and other similar numerical methods, involving fractional derivatives and fractional integral operators
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 624)
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Table of contents (25 chapters)
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Front Matter
About this book
In this monograph the authors present Newton-type, Newton-like and other numerical methods, which involve fractional derivatives and fractional integral operators, for the first time studied in the literature. All for the purpose to solve numerically equations whose associated functions can be also non-differentiable in the ordinary sense. That is among others extending the classical Newton method theory which requires usual differentiability of function.
Chapters are self-contained and can be read independently and several advanced courses can be taught out of this book. An extensive list of references is given per chapter. The book’s results are expected to find applications in many areas of applied mathematics, stochastics, computer science and engineering.As such this monograph is suitable for researchers, graduate students, and seminars of the above subjects, also to be in all science and engineering libraries.
Authors and Affiliations
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Department of Mathematical Sciences, The University of Memphis, Memphis, USA
George A. Anastassiou
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Department of Mathematical Sciences, Cameron University, Lawton, USA
Ioannis K. Argyros
Bibliographic Information
Book Title: Intelligent Numerical Methods: Applications to Fractional Calculus
Authors: George A. Anastassiou, Ioannis K. Argyros
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-319-26721-0
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Hardcover ISBN: 978-3-319-26720-3Published: 15 December 2015
Softcover ISBN: 978-3-319-80003-5Published: 29 March 2019
eBook ISBN: 978-3-319-26721-0Published: 07 December 2015
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVI, 423
Number of Illustrations: 2 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Computational Science and Engineering, Complexity
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