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This book presents an overview of modern Banach space theory. It contains sixteen papers that reflect the wide expanse of the subject. Articles are gathered into five sections according to methodology rather than the topics considered. The sections are: geometrical methods; homological methods; topological methods; operator theoretic methods; and also function space methods. Each section contains survey and research papers describing the state-of-the-art in the topic considered as well as some of the latest most important results. Researchers working in Banach space theory, functional analysis or operator theory will find much of interest here.

Banach spaces --- Functions of complex variables --- Generalized spaces --- Topology --- Methodology --- Banach space theory

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This is an essentially self-contained book on the theory of convex functions and convex optimization in Banach spaces, with a special interest in Orlicz spaces. Approximate algorithms based on the stability principles and the solution of the corresponding nonlinear equations are developed in this text. A synopsis of the geometry of Banach spaces, aspects of stability and the duality of different levels of differentiability and convexity is developed. A particular emphasis is placed on the geometrical aspects of strong solvability of a convex optimization problem: it turns out that this property is equivalent to local uniform convexity of the corresponding convex function. This treatise also provides a novel approach to the fundamental theorems of Variational Calculus based on the principle of pointwise minimization of the Lagrangian on the one hand and convexification by quadratic supplements using the classical Legendre-Ricatti equation on the other. The reader should be familiar with the concepts of mathematical analysis and linear algebra. Some awareness of the principles of measure theory will turn out to be helpful. The book is suitable for students of the second half of undergraduate studies, and it provides a rich set of material for a master course on linear and nonlinear functional analysis. Additionally it offers novel aspects at the advanced level. From the contents: Approximation and Polya Algorithms in Orlicz Spaces Convex Sets and Convex Functions Numerical Treatment of Non-linear Equations and Optimization Problems Stability and Two-stage Optimization Problems Orlicz Spaces, Orlicz Norm and Duality Differentiability and Convexity in Orlicz Spaces Variational Calculus

Stability --- Mathematical optimization. --- Orlicz spaces. --- Spaces, Orlicz --- Ideal spaces --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Dynamics --- Mechanics --- Motion --- Vibration --- Benjamin-Feir instability --- Equilibrium --- Mathematical models. --- Banach space. --- Functional Analysis. --- Optimization. --- Orlicz space. --- Stability.

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Embeddings of discrete metric spaces into Banach spaces recently became an important tool in computer science and topology. The purpose of the book is to present some of the most important techniques and results, mostly on bilipschitz and coarse embeddings. The topics include: (1) Embeddability of locally finite metric spaces into Banach spaces is finitely determined; (2) Constructions of embeddings; (3) Distortion in terms of Poincaré inequalities; (4) Constructions of families of expanders and of families of graphs with unbounded girth and lower bounds on average degrees; (5) Banach spaces which do not admit coarse embeddings of expanders; (6) Structure of metric spaces which are not coarsely embeddable into a Hilbert space; (7) Applications of Markov chains to embeddability problems; (8) Metric characterizations of properties of Banach spaces; (9) Lipschitz free spaces. Substantial part of the book is devoted to a detailed presentation of relevant results of Banach space theory and graph theory. The final chapter contains a list of open problems. Extensive bibliography is also included. Each chapter, except the open problems chapter, contains exercises and a notes and remarks section containing references, discussion of related results, and suggestions for further reading. The book will help readers to enter and to work in a very rapidly developing area having many important connections with different parts of mathematics and computer science.

Banach spaces. --- Lipschitz spaces. --- Stochastic partial differential equations. --- Banach spaces, Stochastic differential equations in --- Hilbert spaces, Stochastic differential equations in --- SPDE (Differential equations) --- Stochastic differential equations in Banach spaces --- Stochastic differential equations in Hilbert spaces --- Differential equations, Partial --- Hölder spaces --- Function spaces --- Functions of complex variables --- Generalized spaces --- Topology --- Banach Space Theory. --- Bilipschitz Embedding. --- Coarse Embedding. --- Embedding of Discrete Metric Spaces. --- Functional Analysis. --- Graph Theory.

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Numerical methods are a specific form of mathematics that involve creating and use of algorithms to map out the mathematical core of a practical problem. Numerical methods naturally find application in all fields of engineering, physical sciences, life sciences, social sciences, medicine, business, and even arts. The common uses of numerical methods include approximation, simulation, and estimation, and there is almost no scientific field in which numerical methods do not find a use. Results communicated here include topics ranging from statistics (Detecting Extreme Values with Order Statistics in Samples from Continuous Distributions) and Statistical software packages (dCATCH—A Numerical Package for d-Variate near G-Optimal Tchakaloff Regression via Fast NNLS) to new approaches for numerical solutions (Exact Solutions to the Maxmin Problem max‖Ax‖ Subject to ‖Bx‖≤1; On q-Quasi-Newton’s Method for Unconstrained Multiobjective Optimization Problems; Convergence Analysis and Complex Geometry of an Efficient Derivative-Free Iterative Method; On Derivative Free Multiple-Root Finders with Optimal Fourth Order Convergence; Finite Integration Method with Shifted Chebyshev Polynomials for Solving Time-Fractional Burgers’ Equations) to the use of wavelets (Orhonormal Wavelet Bases on The 3D Ball Via Volume Preserving Map from the Regular Octahedron) and methods for visualization (A Simple Method for Network Visualization).

Clenshaw–Curtis–Filon --- high oscillation --- singular integral equations --- boundary singularities --- local convergence --- nonlinear equations --- Banach space --- Fréchet-derivative --- finite integration method --- shifted Chebyshev polynomial --- Caputo fractional derivative --- Burgers’ equation --- coupled Burgers’ equation --- maxmin --- supporting vector --- matrix norm --- TMS coil --- optimal geolocation --- probability computing --- Monte Carlo simulation --- order statistics --- extreme values --- outliers --- multiobjective programming --- methods of quasi-Newton type --- Pareto optimality --- q-calculus --- rate of convergence --- wavelets on 3D ball --- uniform 3D grid --- volume preserving map --- Network --- graph drawing --- planar visualizations --- multiple root solvers --- composite method --- weight-function --- derivative-free method --- optimal convergence --- multivariate polynomial regression designs --- G-optimality --- D-optimality --- multiplicative algorithms --- G-efficiency --- Caratheodory-Tchakaloff discrete measure compression --- Non-Negative Least Squares --- accelerated Lawson-Hanson solver

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Solving nonlinear equations in Banach spaces (real or complex nonlinear equations, nonlinear systems, and nonlinear matrix equations, among others), is a non-trivial task that involves many areas of science and technology. Usually the solution is not directly affordable and require an approach using iterative algorithms. This Special Issue focuses mainly on the design, analysis of convergence, and stability of new schemes for solving nonlinear problems and their application to practical problems. Included papers study the following topics: Methods for finding simple or multiple roots either with or without derivatives, iterative methods for approximating different generalized inverses, real or complex dynamics associated to the rational functions resulting from the application of an iterative method on a polynomial. Additionally, the analysis of the convergence has been carried out by means of different sufficient conditions assuring the local, semilocal, or global convergence. This Special issue has allowed us to present the latest research results in the area of iterative processes for solving nonlinear equations as well as systems and matrix equations. In addition to the theoretical papers, several manuscripts on signal processing, nonlinear integral equations, or partial differential equations, reveal the connection between iterative methods and other branches of science and engineering.

Lipschitz condition --- heston model --- rectangular matrices --- computational efficiency --- Hull–White --- order of convergence --- signal and image processing --- dynamics --- divided difference operator --- engineering applications --- smooth and nonsmooth operators --- Newton-HSS method --- higher order method --- Moore–Penrose --- asymptotic error constant --- multiple roots --- higher order --- efficiency index --- multiple-root finder --- computational efficiency index --- Potra–Pták method --- nonlinear equations --- system of nonlinear equations --- purely imaginary extraneous fixed point --- attractor basin --- point projection --- fixed point theorem --- convex constraints --- weight function --- radius of convergence --- Frédholm integral equation --- semi-local convergence --- nonlinear HSS-like method --- convexity --- accretive operators --- Newton-type methods --- multipoint iterations --- banach space --- Kantorovich hypothesis --- variational inequality problem --- Newton method --- semilocal convergence --- least square problem --- Fréchet derivative --- Newton’s method --- iterative process --- Newton-like method --- Banach space --- sixteenth-order optimal convergence --- nonlinear systems --- Chebyshev–Halley-type --- Jarratt method --- iteration scheme --- Newton’s iterative method --- basins of attraction --- drazin inverse --- option pricing --- higher order of convergence --- non-linear equation --- numerical experiment --- signal processing --- optimal methods --- rate of convergence --- n-dimensional Euclidean space --- non-differentiable operator --- projection method --- Newton’s second order method --- intersection --- planar algebraic curve --- Hilbert space --- conjugate gradient method --- sixteenth order convergence method --- Padé approximation --- optimal iterative methods --- error bound --- high order --- Fredholm integral equation --- global convergence --- iterative method --- integral equation --- ?-continuity condition --- systems of nonlinear equations --- generalized inverse --- local convergence --- iterative methods --- multi-valued quasi-nonexpasive mappings --- R-order --- finite difference (FD) --- nonlinear operator equation --- basin of attraction --- PDE --- King’s family --- Steffensen’s method --- nonlinear monotone equations --- Picard-HSS method --- nonlinear models --- the improved curvature circle algorithm --- split variational inclusion problem --- computational order of convergence --- with memory --- multipoint iterative methods --- Kung–Traub conjecture --- multiple zeros --- fourth order iterative methods --- parametric curve --- optimal order --- nonlinear equation