Intelligent Numerical Methods: Applications to Fractional Calculus / by George A Anastassiou, Ioannis K Argyros
By: Anastassiou, George A.
Contributor(s): Argyros, Ioannis K.
Material type:
E-bookSeries: Studies in Computational Intelligence; 624624Publisher: Cham : Springer International Publishing, 2016Edition: 1st ed.Description: 1 recurso en línea (XVI, 423 p.) : 2 ilustraciones col..ISBN: 9783319267210.Subject: Cálculo fraccionario
Summary: 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.
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
|
Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | QA314 .A537 2016 EB (Browse shelf(Opens below)) | .i11589085 | Acceso electrónico | eBOOK .i11589085 |
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.
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