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Mathematical Analysis in Interdisciplinary Research

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Mathematical Analysis in Interdisciplinary Research Synopsis

This contributed volume provides an extensive account of research and expository papers in a broad domain of mathematical analysis and its various applications to a multitude of fields. Presenting the state-of-the-art knowledge in a wide range of topics, the book will be useful to graduate students and researchers in theoretical and applicable interdisciplinary research. The focus is on several subjects including: optimal control problems, optimal maintenance of communication networks, optimal emergency evacuation with uncertainty, cooperative and noncooperative partial differential systems, variational inequalities and general equilibrium models, anisotropic elasticity and harmonic functions, nonlinear stochastic differential equations, operator equations, max-product operators of Kantorovich type, perturbations of operators, integral operators, dynamical systems involving maximal monotone operators, the three-body problem, deceptive systems, hyperbolic equations, strongly generalized preinvex functions, Dirichlet characters, probability distribution functions, applied statistics, integral inequalities, generalized convexity, global hyperbolicity of spacetimes, Douglas-Rachford methods, fixed point problems, the general Rodrigues problem, Banach algebras, affine group, Gibbs semigroup, relator spaces, sparse data representation, Meier-Keeler sequential contractions, hybrid contractions, and polynomial equations.  Some of the works published within this volume provide as well guidelines for further research and proposals for new directions and open problems.

About This Edition

ISBN: 9783030847234
Publication date:
Author: Ioannis N Parasidis
Publisher: Springer Nature Switzerland AG
Format: Paperback
Pagination: 1060 pages
Series: Springer Optimization and Its Applications
Genres: Stochastics
Complex analysis, complex variables
Functional analysis and transforms
Differential calculus and equations
Nonlinear science