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Intelligent Computations: Abstract Fractional Calculus, Inequalities, Approximations
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Artikel-Nr:
9783319669359
Veröffentl:
2017
Einband:
HC runder Rücken kaschiert
Erscheinungsdatum:
12.09.2017
Seiten:
332
Autor:
George A. Anastassiou
Gewicht:
664 g
Format:
241x160x24 mm
Serie:
734, Studies in Computational Intelligence
Sprache:
Englisch
Beschreibung:
This brief book presents the strong fractional analysis of Banach space valued functions of a real domain. The book's results are abstract in nature: analytic inequalities, Korovkin approximation of functions and neural network approximation. The chapters are self-contained and can be read independently.
This concise book is suitable for use in related graduate classes and many research projects. An extensive list of references is provided for each chapter. The book's results are relevant for many areas of pure and applied mathematics. As such, it offers a unique resource for researchers, and a valuable addition to all science and engineering libraries.
This concise book is suitable for use in related graduate classes and many research projects. An extensive list of references is provided for each chapter. The book's results are relevant for many areas of pure and applied mathematics. As such, it offers a unique resource for researchers, and a valuable addition to all science and engineering libraries.
Includes recent original research on abstract fractional calculus, inequalities, and approximations
A strong left Fractional Calculus for Banach space valued functions.- Strong Right Abstract Fractional Calculus.- Strong mixed and generalized Abstract Fractional Calculus.- Foundations of General Fractional Analysis for Banach space valued functions.- Vector abstract fractional Korovkin Approximation.- Basic Abstract Korovkin theory.- High Approximation for Banach space valued functions.- Vectorial abstract fractional approximation using linear operators.- Abstract fractional trigonometric Korovkin approximation.- Multivariate Abstract Approximation for Banach space valued functions.- Arctangent function based Abstract Neural Network approximation.