Lecture Notes on Several Complex Variables
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Computational Geometry – Problem Session Convex Hull & Line Segment Intersection
Computational Geometry { Problem Session Convex Hull & Line Segment Intersection LEHRSTUHL FUR¨ ALGORITHMIK · INSTITUT FUR¨ THEORETISCHE INFORMATIK · FAKULTAT¨ FUR¨ INFORMATIK Guido Bruckner¨ 04.05.2018 Guido Bruckner¨ · Computational Geometry { Problem Session Modus Operandi To register for the oral exam we expect you to present an original solution for at least one problem in the exercise session. • this is about working together • don't worry if your idea doesn't work! Guido Bruckner¨ · Computational Geometry { Problem Session Outline Convex Hull Line Segment Intersection Guido Bruckner¨ · Computational Geometry { Problem Session Definition of Convex Hull Def: A region S ⊆ R2 is called convex, when for two points p; q 2 S then line pq 2 S. The convex hull CH(S) of S is the smallest convex region containing S. Guido Bruckner¨ · Computational Geometry { Problem Session Definition of Convex Hull Def: A region S ⊆ R2 is called convex, when for two points p; q 2 S then line pq 2 S. The convex hull CH(S) of S is the smallest convex region containing S. Guido Bruckner¨ · Computational Geometry { Problem Session Definition of Convex Hull Def: A region S ⊆ R2 is called convex, when for two points p; q 2 S then line pq 2 S. The convex hull CH(S) of S is the smallest convex region containing S. In physics: Guido Bruckner¨ · Computational Geometry { Problem Session Definition of Convex Hull Def: A region S ⊆ R2 is called convex, when for two points p; q 2 S then line pq 2 S. The convex hull CH(S) of S is the smallest convex region containing S. -
New Hermite–Hadamard and Jensen Inequalities for Log-H-Convex
International Journal of Computational Intelligence Systems (2021) 14:155 https://doi.org/10.1007/s44196-021-00004-1 RESEARCH ARTICLE New Hermite–Hadamard and Jensen Inequalities for Log‑h‑Convex Fuzzy‑Interval‑Valued Functions Muhammad Bilal Khan1 · Lazim Abdullah2 · Muhammad Aslam Noor1 · Khalida Inayat Noor1 Received: 9 December 2020 / Accepted: 23 July 2021 © The Author(s) 2021 Abstract In the preset study, we introduce the new class of convex fuzzy-interval-valued functions which is called log-h-convex fuzzy-interval-valued functions (log-h-convex FIVFs) by means of fuzzy order relation. We have also investigated some properties of log-h-convex FIVFs. Using this class, we present Jensen and Hermite–Hadamard inequalities (HH-inequalities). Moreover, some useful examples are presented to verify HH-inequalities for log-h-convex FIVFs. Several new and known special results are also discussed which can be viewed as an application of this concept. Keywords Fuzzy-interval-valued functions · Log-h-convex · Hermite–Hadamard inequality · Hemite–Hadamard–Fejér inequality · Jensen’s inequality 1 Introduction was independently introduced by Hadamard, see [24, 25, 31]. It can be expressed in the following way: The theory of convexity in pure and applied sciences has Let Ψ∶K → ℝ be a convex function on a convex set K become a rich source of inspiration. In several branches of and , ∈ K with ≤ . Then, mathematical and engineering sciences, this theory had not only inspired new and profound results, but also ofers a + 1 Ψ ≤ Ψ()d coherent and general basis for studying a wide range of prob- 2 − � lems. Many new notions of convexity have been developed Ψ()+Ψ() and investigated for convex functions and convex sets. -
CORE View Metadata, Citation and Similar Papers at Core.Ac.Uk
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Bulgarian Digital Mathematics Library at IMI-BAS Serdica Math. J. 27 (2001), 203-218 FIRST ORDER CHARACTERIZATIONS OF PSEUDOCONVEX FUNCTIONS Vsevolod Ivanov Ivanov Communicated by A. L. Dontchev Abstract. First order characterizations of pseudoconvex functions are investigated in terms of generalized directional derivatives. A connection with the invexity is analysed. Well-known first order characterizations of the solution sets of pseudolinear programs are generalized to the case of pseudoconvex programs. The concepts of pseudoconvexity and invexity do not depend on a single definition of the generalized directional derivative. 1. Introduction. Three characterizations of pseudoconvex functions are considered in this paper. The first is new. It is well-known that each pseudo- convex function is invex. Then the following question arises: what is the type of 2000 Mathematics Subject Classification: 26B25, 90C26, 26E15. Key words: Generalized convexity, nonsmooth function, generalized directional derivative, pseudoconvex function, quasiconvex function, invex function, nonsmooth optimization, solution sets, pseudomonotone generalized directional derivative. 204 Vsevolod Ivanov Ivanov the function η from the definition of invexity, when the invex function is pseudo- convex. This question is considered in Section 3, and a first order necessary and sufficient condition for pseudoconvexity of a function is given there. It is shown that the class of strongly pseudoconvex functions, considered by Weir [25], coin- cides with pseudoconvex ones. The main result of Section 3 is applied to characterize the solution set of a nonlinear programming problem in Section 4. The base results of Jeyakumar and Yang in the paper [13] are generalized there to the case, when the function is pseudoconvex. -
On the Ekeland Variational Principle with Applications and Detours
Lectures on The Ekeland Variational Principle with Applications and Detours By D. G. De Figueiredo Tata Institute of Fundamental Research, Bombay 1989 Author D. G. De Figueiredo Departmento de Mathematica Universidade de Brasilia 70.910 – Brasilia-DF BRAZIL c Tata Institute of Fundamental Research, 1989 ISBN 3-540- 51179-2-Springer-Verlag, Berlin, Heidelberg. New York. Tokyo ISBN 0-387- 51179-2-Springer-Verlag, New York. Heidelberg. Berlin. Tokyo No part of this book may be reproduced in any form by print, microfilm or any other means with- out written permission from the Tata Institute of Fundamental Research, Colaba, Bombay 400 005 Printed by INSDOC Regional Centre, Indian Institute of Science Campus, Bangalore 560012 and published by H. Goetze, Springer-Verlag, Heidelberg, West Germany PRINTED IN INDIA Preface Since its appearance in 1972 the variational principle of Ekeland has found many applications in different fields in Analysis. The best refer- ences for those are by Ekeland himself: his survey article [23] and his book with J.-P. Aubin [2]. Not all material presented here appears in those places. Some are scattered around and there lies my motivation in writing these notes. Since they are intended to students I included a lot of related material. Those are the detours. A chapter on Nemyt- skii mappings may sound strange. However I believe it is useful, since their properties so often used are seldom proved. We always say to the students: go and look in Krasnoselskii or Vainberg! I think some of the proofs presented here are more straightforward. There are two chapters on applications to PDE. -
15 BASIC PROPERTIES of CONVEX POLYTOPES Martin Henk, J¨Urgenrichter-Gebert, and G¨Unterm
15 BASIC PROPERTIES OF CONVEX POLYTOPES Martin Henk, J¨urgenRichter-Gebert, and G¨unterM. Ziegler INTRODUCTION Convex polytopes are fundamental geometric objects that have been investigated since antiquity. The beauty of their theory is nowadays complemented by their im- portance for many other mathematical subjects, ranging from integration theory, algebraic topology, and algebraic geometry to linear and combinatorial optimiza- tion. In this chapter we try to give a short introduction, provide a sketch of \what polytopes look like" and \how they behave," with many explicit examples, and briefly state some main results (where further details are given in subsequent chap- ters of this Handbook). We concentrate on two main topics: • Combinatorial properties: faces (vertices, edges, . , facets) of polytopes and their relations, with special treatments of the classes of low-dimensional poly- topes and of polytopes \with few vertices;" • Geometric properties: volume and surface area, mixed volumes, and quer- massintegrals, including explicit formulas for the cases of the regular simplices, cubes, and cross-polytopes. We refer to Gr¨unbaum [Gr¨u67]for a comprehensive view of polytope theory, and to Ziegler [Zie95] respectively to Gruber [Gru07] and Schneider [Sch14] for detailed treatments of the combinatorial and of the convex geometric aspects of polytope theory. 15.1 COMBINATORIAL STRUCTURE GLOSSARY d V-polytope: The convex hull of a finite set X = fx1; : : : ; xng of points in R , n n X i X P = conv(X) := λix λ1; : : : ; λn ≥ 0; λi = 1 : i=1 i=1 H-polytope: The solution set of a finite system of linear inequalities, d T P = P (A; b) := x 2 R j ai x ≤ bi for 1 ≤ i ≤ m ; with the extra condition that the set of solutions is bounded, that is, such that m×d there is a constant N such that jjxjj ≤ N holds for all x 2 P . -
Chapter 5 Convex Optimization in Function Space 5.1 Foundations of Convex Analysis
Chapter 5 Convex Optimization in Function Space 5.1 Foundations of Convex Analysis Let V be a vector space over lR and k ¢ k : V ! lR be a norm on V . We recall that (V; k ¢ k) is called a Banach space, if it is complete, i.e., if any Cauchy sequence fvkglN of elements vk 2 V; k 2 lN; converges to an element v 2 V (kvk ¡ vk ! 0 as k ! 1). Examples: Let be a domain in lRd; d 2 lN. Then, the space C() of continuous functions on is a Banach space with the norm kukC() := sup ju(x)j : x2 The spaces Lp(); 1 · p < 1; of (in the Lebesgue sense) p-integrable functions are Banach spaces with the norms Z ³ ´1=p p kukLp() := ju(x)j dx : The space L1() of essentially bounded functions on is a Banach space with the norm kukL1() := ess sup ju(x)j : x2 The (topologically and algebraically) dual space V ¤ is the space of all bounded linear functionals ¹ : V ! lR. Given ¹ 2 V ¤, for ¹(v) we often write h¹; vi with h¢; ¢i denoting the dual product between V ¤ and V . We note that V ¤ is a Banach space equipped with the norm j h¹; vi j k¹k := sup : v2V nf0g kvk Examples: The dual of C() is the space M() of Radon measures ¹ with Z h¹; vi := v d¹ ; v 2 C() : The dual of L1() is the space L1(). The dual of Lp(); 1 < p < 1; is the space Lq() with q being conjugate to p, i.e., 1=p + 1=q = 1. -
First Order Characterizations of Pseudoconvex Functions
Serdica Math. J. 27 (2001), 203-218 FIRST ORDER CHARACTERIZATIONS OF PSEUDOCONVEX FUNCTIONS Vsevolod Ivanov Ivanov Communicated by A. L. Dontchev Abstract. First order characterizations of pseudoconvex functions are investigated in terms of generalized directional derivatives. A connection with the invexity is analysed. Well-known first order characterizations of the solution sets of pseudolinear programs are generalized to the case of pseudoconvex programs. The concepts of pseudoconvexity and invexity do not depend on a single definition of the generalized directional derivative. 1. Introduction. Three characterizations of pseudoconvex functions are considered in this paper. The first is new. It is well-known that each pseudo- convex function is invex. Then the following question arises: what is the type of 2000 Mathematics Subject Classification: 26B25, 90C26, 26E15. Key words: Generalized convexity, nonsmooth function, generalized directional derivative, pseudoconvex function, quasiconvex function, invex function, nonsmooth optimization, solution sets, pseudomonotone generalized directional derivative. 204 Vsevolod Ivanov Ivanov the function η from the definition of invexity, when the invex function is pseudo- convex. This question is considered in Section 3, and a first order necessary and sufficient condition for pseudoconvexity of a function is given there. It is shown that the class of strongly pseudoconvex functions, considered by Weir [25], coin- cides with pseudoconvex ones. The main result of Section 3 is applied to characterize the solution set of a nonlinear programming problem in Section 4. The base results of Jeyakumar and Yang in the paper [13] are generalized there to the case, when the function is pseudoconvex. The second and third characterizations are considered in Sections 5, 6. -
Extremal Positive Pluriharmonic Functions on Euclidean Balls
EXTREMAL POSITIVE PLURIHARMONIC FUNCTIONS ON EUCLIDEAN BALLS By Farhad Jafari and Mihai Putinar IMA Preprint Series # 2180 ( November 2007 ) INSTITUTE FOR MATHEMATICS AND ITS APPLICATIONS UNIVERSITY OF MINNESOTA 400 Lind Hall 207 Church Street S.E. Minneapolis, Minnesota 55455–0436 Phone: 612-624-6066 Fax: 612-626-7370 URL: http://www.ima.umn.edu EXTREMAL POSITIVE PLURIHARMONIC FUNCTIONS ON EUCLIDEAN BALLS FARHAD JAFARI AND MIHAI PUTINAR To Professor J. J. Kohn on the occasion of his seventy-fifth birthday Abstract. Contrary to the well understood structure of positive har- monic functions in the unit disk, most of the properties of positive pluri- n harmonic functions in symmetric domains of C , in particular the unit ball, remain mysterious. In particular, in spite of efforts spread over quite a few decades, no characterization of the extremal rays in the n cone of positive pluriharmonic functions in the unit ball of C is known. We investigate this question by a geometric tomography technique, and provide some new classes of examples of such extremal functions. 1. Introduction. According to a classical theorem due to Herglotz and F. Riesz, every non- negative harmonic function in the open unit disk D is the Poisson integral of a positive Borel measure on the unit circle T. This correspondence readily characterizes the extreme points of the convex cone of positive harmonic functions h in D, normalized by the condition h(0) = 1, as the Poisson integrals of extremal probability measures on the unit circle, namely the Dirac measures on the unit circle. Thus these extremal objects are simply the one-parameter class of functions uζ (z) = P (z, ζ), ζ ∈ T, where P (z, ζ) is the classical Poisson kernel in D. -
Characterizations of Quasiconvex Functions and Pseudomonotonicity of Subdifferentials
J. Appl. Environ. Biol. Sci. , 5(6)358-364, 2015 ISSN: 2090-4274 Journal of Applied Environmental © 2015, TextRoad Publication and Biological Sciences www.textroad.com Characterizations of Quasiconvex Functions and Pseudomonotonicity of Subdifferentials Somayeh Yazdani Department of Mathematics, Faculty of Basic Sciences, Nour Branch, Islamic Azad University, Nour, Iran. Received: January 6, 2015 Accepted: March 10, 2015 ABSTRACT In this paper we introduce the concepts of quasimonotone maps and pseudoconvex functions. Moreover, a notion of pseudomonotonicity for multi mappings is introduced; it is shown that, if a function f is continuous, then its pseudoconvexity is equivalent to the pseudomonotonicity of its generalized subdifferential in the sense of Clarke and Rockafellar and prove that a lower semicontinuous function on an infinite dimensional space is quasiconvex if and only if its generalized subdifferential is quasimonotone. KEYWORDS: Quasiconvex functions, pseudoconvex functions, quasimonotone maps, pseudo monotone maps, generalized subdifferentials. I. INTRODUCTION As far as we know quasiconvex functions were first mentioned by Finetti in 1949,[ Finetti,1949]. Since then much effort has been focused on the study of this class of functions for they have much in common with convex functions. One of the most important properties of convex functions is that their level sets are convex . Mapping of the monograph theory in the beginning of methods were obtained in spaces with more banach efforts and evaluation background lightness for the relationship between monograhy on a map and the linkage of premise was created. This study was performed to uniform of non-linear mappings and differential relations and was paid uniformity. The purpose of this paper is to declare these powerful tools and new applications of it in a function in the analysis of the last few decades. -
The Krein–Milman Theorem a Project in Functional Analysis
The Krein{Milman Theorem A Project in Functional Analysis Samuel Pettersson November 29, 2016 2. Extreme points 3. The Krein{Milman theorem 4. An application Outline 1. An informal example 3. The Krein{Milman theorem 4. An application Outline 1. An informal example 2. Extreme points 4. An application Outline 1. An informal example 2. Extreme points 3. The Krein{Milman theorem Outline 1. An informal example 2. Extreme points 3. The Krein{Milman theorem 4. An application Outline 1. An informal example 2. Extreme points 3. The Krein{Milman theorem 4. An application Convex sets and their \corners" Observation Some convex sets are the convex hulls of their \corners". Convex sets and their \corners" Observation Some convex sets are the convex hulls of their \corners". kxk1≤ 1 Convex sets and their \corners" Observation Some convex sets are the convex hulls of their \corners". kxk1≤ 1 Convex sets and their \corners" Observation Some convex sets are the convex hulls of their \corners". kxk1≤ 1 kxk2≤ 1 Convex sets and their \corners" Observation Some convex sets are the convex hulls of their \corners". kxk1≤ 1 kxk2≤ 1 Convex sets and their \corners" Observation Some convex sets are the convex hulls of their \corners". kxk1≤ 1 kxk2≤ 1 kxk1≤ 1 Convex sets and their \corners" Observation Some convex sets are the convex hulls of their \corners". kxk1≤ 1 kxk2≤ 1 kxk1≤ 1 x1; x2 ≥ 0 Convex sets and their \corners" Observation Some convex sets are not the convex hulls of their \corners". Convex sets and their \corners" Observation Some convex sets are not the convex hulls of their \corners". -
Convexity in Oriented Matroids
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector JOURNAL OF COMBINATORIAL THEORY, Series B 29, 231-243 (1980) Convexity in Oriented Matroids MICHEL LAS VERGNAS C.N.R.S., Universite’ Pierre et Marie Curie, U.E.R. 48, 4 place Jussieu, 75005 Paris, France Communicated by the Editors Received June 11, 1974 We generalize to oriented matroids classical notions of Convexity Theory: faces of convex polytopes, convex hull, etc., and prove some basic properties. We relate the number of acyclic orientations of an orientable matroid to an evaluation of its Tutte polynomial. The structure of oriented matroids (oriented combinatorial geometries) [ 1 ] retains many properties of vector spaces over ordered fields. In the present paper we consider classical notions such as those of faces of convex polytopes, convex hull, etc., and show that usual definitions can be extended to finite oriented matroids in a natural way. We prove some basic properties: lattice structure with chain property of the set of faces of an acyclic oriented matroid, lower bounds for the numbers of vertices and facets and charac- terization of extremal cases, analogues of the Krein-Milman Theorem. In Section 3 we relate the number of acyclic orientations of an orientable matroid A4 to the evaluation t(M; 2,0) of its Tutte polynomial. The present paper is a sequel to [ 11. Its content constituted originally Sections 6, 7 and 8 of “MatroYdes orientables” (preprint, April 1974) [8]. Basic notions on oriented matroids are given in [ 11. For completeness we recall the main definitions [ 1, Theorems 2.1 and 2.21: All considered matroids are on finite sets. -
Characterizing Strong Pseudoconvexity, Obstructions to Biholomorphisms, and Lyapunov Exponents
Mathematische Annalen (2019) 374:1811–1844 https://doi.org/10.1007/s00208-018-1715-7 Mathematische Annalen Characterizing strong pseudoconvexity, obstructions to biholomorphisms, and Lyapunov exponents Andrew Zimmer1 Received: 23 March 2017 / Revised: 21 February 2018 / Published online: 27 June 2018 © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract In this paper we consider the following question: For bounded domains with smooth boundary, can strong pseudoconvexity be characterized in terms of the intrinsic com- plex geometry of the domain? Our approach to answering this question is based on understanding the dynamical behavior of real geodesics in the Kobayashi metric and allows us to prove a number of results for domains with low regularity. For instance, we show that for convex domains with C2, boundary strong pseudoconvexity can be characterized in terms of the behavior of the squeezing function near the boundary, the behavior of the holomorphic sectional curvature of the Bergman metric near the boundary, or any other reasonable measure of the complex geometry near the bound- ary. The first characterization gives a partial answer to a question of Fornæss and Wold. As an application of these characterizations, we show that a convex domain with C2, boundary which is biholomorphic to a strongly pseudoconvex domain is also strongly pseudoconvex. 1 Introduction A domain in Cd with C2 boundary is called strongly pseudoconvex if the Levi form of the boundary is positive definite. The Levi form is extrinsic and in this paper we study the following question: Question 1 For domains with C2 boundary, can strong pseudoconvexity be character- ized in terms of the intrinsic complex geometry of the domain? Although strongly pseudoconvex domains form one of the most important classes of domains in several complex variables, it does not appear that Question 1 has been Communicated by Ngaiming Mok.