Nonlinearity: Ordinary and Fractional Approximations by Sublinear and Max-Product Operators

• Κύριος συγγραφέας: Anastassiou, George A. (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: Studies in Systems, Decision and Control, 147
• Θέματα: Computational complexity.; Computational intelligence.; Complexity.; Computational Intelligence.

 This book focuses on approximations under the presence of ordinary and fractional smoothness, presenting both the univariate and multivariate cases. It also explores approximations under convexity and a new trend in approximation theory -approximation by sublinear operators with applications to max-product operators, which are nonlinear and rational providing very fast and flexible approximations. The results presented have applications in numerous areas of pure and applied mathematics, especially in approximation theory and numerical analysis in both ordinary and fractional senses. As such this book is suitable for researchers, graduate students, and seminars of the above disciplines, and is a must for all science and engineering libraries. 

 Approximation by Positive Sublinear Operators -- High order Approximation by Max-Product Operators -- Conformable Fractional Approximations using Max-Product operators -- Caputo Fractional Approximation using positive Sublinear operators -- Canavati Fractional Approximations using Max-product operators -- Iterated Fractional Approximations using Max-product operators -- Mixed Conformable Fractional Approximation using Positive Sublinear Operators -- Approximation of Fuzzy numbers using Max-product operators -- High Order Approximation by Multivariate Sublinear and Max-product Operators -- High Order Approximation by Sublinear and Max-product Operators using Convexity -- High Order Conformable Fractional Approximation by Max-Product Operators using Convexity -- High Order Approximation by Multivariate Sublinear and Max-product Operators under Convexity.