Anastassiou / Argyros Functional Numerical Methods: Applications to Abstract Fractional Calculus

1. Auflage 2018
ISBN: 978-3-319-69526-6
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: Wasserzeichen (»Systemvoraussetzungen)

E-Book, Englisch, Band 130, 161 Seiten, eBook

Reihe: Studies in Systems, Decision and Control

This book presents applications of Newton-like and other similar methods to solve abstract functional equations involving fractional derivatives. It focuses on Banach space-valued functions of a real domain – studied for the first time in the literature. Various issues related to the modeling and analysis of fractional order systems continue to grow in popularity, and the book provides a deeper and more formal analysis of selected issues that are relevant to many areas – including decision-making, complex processes, systems modeling and control – and deeply embedded in the fields of engineering, computer science, physics, economics, and the social and life sciences. The book offers a valuable resource for researchers and graduate students, and can also be used as a textbook for seminars on the above-mentioned subjects. All chapters are self-contained and can be read independently. Further, each chapter includes an extensive list of references.

Zielgruppe

Research

Autoren/Hrsg.

Anastassiou, George A.

Argyros, Ioannis K.

Inhaltsverzeichnis

Explicit-Implicit methods with applications to Banach space valued functions in abstract fractional calculus.- Convergence of Iterative methods in abstract fractional calculus.- Equations for Banach space valued functions in fractional vector calculi.- Iterative methods in abstract fractional calculus.- Semi-local convergence in right abstract fractional calculus.- Algorithmic convergence in abstract g-fractional calculus.- Iterative procedures for solving equations in abstract fractional calculus.- Approximate solutions of equations in abstract g-fractional calculus.- Generating sequences for solving in abstract g-fractional calculus.- Numerical Optimization and fractional invexity.