Studies in Computational Intelligence 734 George A. Anastassiou Intelligent Computations: Abstract Fractional Calculus, Inequalities, Approximations Studies in Computational Intelligence Volume 734 Series editor Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland e-mail: [email protected] About this Series The series “Studies in Computational Intelligence” (SCI) publishes new develop- mentsandadvancesinthevariousareasofcomputationalintelligence—quicklyand with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life sciences, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output. More information about this series at http://www.springer.com/series/7092 George A. Anastassiou Intelligent Computations: Abstract Fractional Calculus, Inequalities, Approximations 123 George A.Anastassiou Department ofMathematical Sciences University of Memphis Memphis,TN USA ISSN 1860-949X ISSN 1860-9503 (electronic) Studies in Computational Intelligence ISBN978-3-319-66935-9 ISBN978-3-319-66936-6 (eBook) DOI 10.1007/978-3-319-66936-6 LibraryofCongressControlNumber:2017951144 ©SpringerInternationalPublishingAG2018 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpart of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission orinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilar methodologynowknownorhereafterdeveloped. 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Printedonacid-freepaper ThisSpringerimprintispublishedbySpringerNature TheregisteredcompanyisSpringerInternationalPublishingAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland To My Family Preface This rather brief monograph is regarding the fractional analysis of Banach space valued functions of a real domain. It is the natural evolution of recent author’s researchworkputinabookformforthefirsttime.Theauthoristhefounderofthe so-called strong theory offractional calculus at abstract level. Usual vector-valued differentiationresemblesthenumericalone,andintegralshereareofBochnertype. We apply our theory extensively to abstract analytic inequalities and abstract Korovkin approximation offunctions, as well as abstract neural network approxi- mation. By using Bochner integral properties, we present a left and right Caputo-type, as well as Canavati-type, strong fractional theory which is the direct analog of the real one, but now dealing with Banach space valued functions. In the literature, there are very few articles about the weak fractional theory of Banach space valued functions. However, we found that the weak theory, using Pettis integral and functionals, is complicated, less clear, difficult, uncomfortable and unnecessary. Withthismonograph,wetrytosimplifymattersandputtherelatedtheoryonits natural grounds and resemble the theory on real numbers. Here, chapters are self-contained and can be read independently. This concise monograph is suitable to be used in related graduate classes and many research projects. The list of presented topics follows: strong left fractional calculus for Banach space valued functions, strong right fractional calculus for Banach space valued functions, strongmixedandgeneralizedfractionalcalculusforBanachspacevaluedfunctions, principles of general fractional analysis for Banach space valued functions, basic Korovkin theory for Banach space valued functions, vector fractional Korovkin-type approximations, high-order approximation theory for Banach space valued functions, vectorial fractional approximation by using linear operators, vector fractional trigonometric Korovkin approximation, multivariate and abstract approximation theory for Banach space valued functions, vii viii Preface arctangent function-based Banach space valued neural network approximation, An extensive list of references is given per chapter. The book’s results are expected to find applications in many areas of pure and applied mathematics, especially in fractional ordinary and partial differential equationsandfractionalnumericalanalysis.Assuch,thismonographissuitablefor researchers, graduate students and seminars of the above disciplines, also to be in all science and engineering libraries. Thepreparationofthisbooktookplaceduringtheacademicyear2016–2017at the University of Memphis. The author likes to thank Prof. Alina Lupas of University of Oradea, Romania, for checking and reading the manuscript. Memphis, USA George A. Anastassiou May 2017 Contents 1 A Strong Left Fractional Calculus for Banach Space Valued Functions. .... .... .... ..... .... .... .... .... .... ..... .... 1 1.1 Introduction .. .... ..... .... .... .... .... .... ..... .... 1 1.2 Main Results.. .... ..... .... .... .... .... .... ..... .... 2 References. .... .... .... ..... .... .... .... .... .... ..... .... 31 2 Strong Right Abstract Fractional Calculus... .... .... ..... .... 33 2.1 Introduction .. .... ..... .... .... .... .... .... ..... .... 33 2.2 Main Results.. .... ..... .... .... .... .... .... ..... .... 34 References. .... .... .... ..... .... .... .... .... .... ..... .... 63 3 Strong Mixed and Generalized Abstract Fractional Calculus . .... 65 3.1 Introduction .. .... ..... .... .... .... .... .... ..... .... 65 3.2 Main Results.. .... ..... .... .... .... .... .... ..... .... 66 References. .... .... .... ..... .... .... .... .... .... ..... .... 85 4 Foundations of General Fractional Analysis for Banach Space Valued Functions... .... ..... .... .... .... .... .... ..... .... 87 4.1 Introduction .. .... ..... .... .... .... .... .... ..... .... 87 4.2 Auxilliary Results.. ..... .... .... .... .... .... ..... .... 89 4.3 Main Results.. .... ..... .... .... .... .... .... ..... .... 98 4.4 Applications .. .... ..... .... .... .... .... .... ..... .... 141 References. .... .... .... ..... .... .... .... .... .... ..... .... 145 5 Vector Abstract Fractional Korovkin Approximation .. ..... .... 147 5.1 Introduction .. .... ..... .... .... .... .... .... ..... .... 147 5.2 Background .. .... ..... .... .... .... .... .... ..... .... 150 5.3 Main Results.. .... ..... .... .... .... .... .... ..... .... 161 5.4 Application... .... ..... .... .... .... .... .... ..... .... 170 References. .... .... .... ..... .... .... .... .... .... ..... .... 172 ix x Contents 6 Basic Abstract Korovkin Theory... .... .... .... .... ..... .... 175 6.1 Motivation ... .... ..... .... .... .... .... .... ..... .... 175 6.2 Main Results.. .... ..... .... .... .... .... .... ..... .... 177 References. .... .... .... ..... .... .... .... .... .... ..... .... 188 7 High Approximation for Banach Space Valued Functions.... .... 189 7.1 Motivation ... .... ..... .... .... .... .... .... ..... .... 189 7.2 Main Results.. .... ..... .... .... .... .... .... ..... .... 191 References. .... .... .... ..... .... .... .... .... .... ..... .... 210 8 Vectorial Abstract Fractional Approximation Using Linear Operators. .... .... .... ..... .... .... .... .... .... ..... .... 211 8.1 Motivation ... .... ..... .... .... .... .... .... ..... .... 211 8.2 Background .. .... ..... .... .... .... .... .... ..... .... 213 8.3 Main Results.. .... ..... .... .... .... .... .... ..... .... 219 8.4 Application... .... ..... .... .... .... .... .... ..... .... 231 References. .... .... .... ..... .... .... .... .... .... ..... .... 233 9 Abstract Fractional Trigonometric Korovkin Approximation . .... 235 9.1 Motivation ... .... ..... .... .... .... .... .... ..... .... 235 9.2 Background .. .... ..... .... .... .... .... .... ..... .... 237 9.3 Main Results.. .... ..... .... .... .... .... .... ..... .... 244 9.4 Application... .... ..... .... .... .... .... .... ..... .... 255 References. .... .... .... ..... .... .... .... .... .... ..... .... 259 10 Multivariate Abstract Approximation for Banach Space Valued Functions. .... .... .... ..... .... .... .... .... .... ..... .... 261 10.1 Motivation ... .... ..... .... .... .... .... .... ..... .... 261 10.2 Background .. .... ..... .... .... .... .... .... ..... .... 263 10.3 Main Results.. .... ..... .... .... .... .... .... ..... .... 268 10.4 Application... .... ..... .... .... .... .... .... ..... .... 279 References. .... .... .... ..... .... .... .... .... .... ..... .... 281 11 Arctangent Function Based Abstract Neural Network Approximation. .... .... ..... .... .... .... .... .... ..... .... 283 11.1 Introduction .. .... ..... .... .... .... .... .... ..... .... 283 11.2 Basics... .... .... ..... .... .... .... .... .... ..... .... 284 11.3 Main Results.. .... ..... .... .... .... .... .... ..... .... 293 References. .... .... .... ..... .... .... .... .... .... ..... .... 319