Lecture 8: Baire Category Theorem and Uniform Boundedness Principle
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												  On Quasi Norm Attaining Operators Between Banach SpacesON QUASI NORM ATTAINING OPERATORS BETWEEN BANACH SPACES GEUNSU CHOI, YUN SUNG CHOI, MINGU JUNG, AND MIGUEL MART´IN Abstract. We provide a characterization of the Radon-Nikod´ymproperty in terms of the denseness of bounded linear operators which attain their norm in a weak sense, which complement the one given by Bourgain and Huff in the 1970's. To this end, we introduce the following notion: an operator T : X ÝÑ Y between the Banach spaces X and Y is quasi norm attaining if there is a sequence pxnq of norm one elements in X such that pT xnq converges to some u P Y with }u}“}T }. Norm attaining operators in the usual (or strong) sense (i.e. operators for which there is a point in the unit ball where the norm of its image equals the norm of the operator) and also compact operators satisfy this definition. We prove that strong Radon-Nikod´ymoperators can be approximated by quasi norm attaining operators, a result which does not hold for norm attaining operators in the strong sense. This shows that this new notion of quasi norm attainment allows to characterize the Radon-Nikod´ymproperty in terms of denseness of quasi norm attaining operators for both domain and range spaces, completing thus a characterization by Bourgain and Huff in terms of norm attaining operators which is only valid for domain spaces and it is actually false for range spaces (due to a celebrated example by Gowers of 1990). A number of other related results are also included in the paper: we give some positive results on the denseness of norm attaining Lipschitz maps, norm attaining multilinear maps and norm attaining polynomials, characterize both finite dimensionality and reflexivity in terms of quasi norm attaining operators, discuss conditions to obtain that quasi norm attaining operators are actually norm attaining, study the relationship with the norm attainment of the adjoint operator and, finally, present some stability results.
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												  Uniform Boundedness Principle for Unbounded OperatorsUNIFORM BOUNDEDNESS PRINCIPLE FOR UNBOUNDED OPERATORS C. GANESA MOORTHY and CT. RAMASAMY Abstract. A uniform boundedness principle for unbounded operators is derived. A particular case is: Suppose fTigi2I is a family of linear mappings of a Banach space X into a normed space Y such that fTix : i 2 Ig is bounded for each x 2 X; then there exists a dense subset A of the open unit ball in X such that fTix : i 2 I; x 2 Ag is bounded. A closed graph theorem and a bounded inverse theorem are obtained for families of linear mappings as consequences of this principle. Some applications of this principle are also obtained. 1. Introduction There are many forms for uniform boundedness principle. There is no known evidence for this principle for unbounded operators which generalizes classical uniform boundedness principle for bounded operators. The second section presents a uniform boundedness principle for unbounded operators. An application to derive Hellinger-Toeplitz theorem is also obtained in this section. A JJ J I II closed graph theorem and a bounded inverse theorem are obtained for families of linear mappings in the third section as consequences of this principle. Go back Let us assume the following: Every vector space X is over R or C. An α-seminorm (0 < α ≤ 1) is a mapping p: X ! [0; 1) such that p(x + y) ≤ p(x) + p(y), p(ax) ≤ jajαp(x) for all x; y 2 X Full Screen Close Received November 7, 2013. 2010 Mathematics Subject Classification. Primary 46A32, 47L60. Key words and phrases.
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												  On the Boundary Between Mereology and TopologyOn the Boundary Between Mereology and Topology Achille C. Varzi Istituto per la Ricerca Scientifica e Tecnologica, I-38100 Trento, Italy [email protected] (Final version published in Roberto Casati, Barry Smith, and Graham White (eds.), Philosophy and the Cognitive Sciences. Proceedings of the 16th International Wittgenstein Symposium, Vienna, Hölder-Pichler-Tempsky, 1994, pp. 423–442.) 1. Introduction Much recent work aimed at providing a formal ontology for the common-sense world has emphasized the need for a mereological account to be supplemented with topological concepts and principles. There are at least two reasons under- lying this view. The first is truly metaphysical and relates to the task of charac- terizing individual integrity or organic unity: since the notion of connectedness runs afoul of plain mereology, a theory of parts and wholes really needs to in- corporate a topological machinery of some sort. The second reason has been stressed mainly in connection with applications to certain areas of artificial in- telligence, most notably naive physics and qualitative reasoning about space and time: here mereology proves useful to account for certain basic relation- ships among things or events; but one needs topology to account for the fact that, say, two events can be continuous with each other, or that something can be inside, outside, abutting, or surrounding something else. These motivations (at times combined with others, e.g., semantic transpar- ency or computational efficiency) have led to the development of theories in which both mereological and topological notions play a pivotal role. How ex- actly these notions are related, however, and how the underlying principles should interact with one another, is still a rather unexplored issue.
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												  Baire Category Theorem and Uniform Boundedness Principle)Functional Analysis (WS 19/20), Problem Set 3 (Baire Category Theorem and Uniform Boundedness Principle) Baire Category Theorem B1. Let (X; k·kX ) be an innite dimensional Banach space. Prove that X has uncountable Hamel basis. Note: This is Problem A2 from Problem Set 1. B2. Consider subset of bounded sequences 1 A = fx 2 l : only nitely many xk are nonzerog : Can one dene a norm on A so that it becomes a Banach space? Consider the same question with the set of polynomials dened on interval [0; 1]. B3. Prove that the set L2(0; 1) has empty interior as the subset of Banach space L1(0; 1). B4. Let f : [0; 1) ! [0; 1) be a continuous function such that for every x 2 [0; 1), f(kx) ! 0 as k ! 1. Prove that f(x) ! 0 as x ! 1. B5.( Uniform Boundedness Principle) Let (X; k · kX ) be a Banach space and (Y; k · kY ) be a normed space. Let fTαgα2A be a family of bounded linear operators between X and Y . Suppose that for any x 2 X, sup kTαxkY < 1: α2A Prove that . supα2A kTαk < 1 Uniform Boundedness Principle U1. Let F be a normed space C[0; 1] with L2(0; 1) norm. Check that the formula 1 Z n 'n(f) = n f(t) dt 0 denes a bounded linear functional on . Verify that for every , F f 2 F supn2N j'n(f)j < 1 but . Why Uniform Boundedness Principle is not satised in this case? supn2N k'nk = 1 U2.( pointwise convergence of operators) Let (X; k · kX ) be a Banach space and (Y; k · kY ) be a normed space.
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												  FUNCTIONAL ANALYSIS 1. Banach and Hilbert Spaces in WhatFUNCTIONAL ANALYSIS PIOTR HAJLASZ 1. Banach and Hilbert spaces In what follows K will denote R of C. Definition. A normed space is a pair (X, k · k), where X is a linear space over K and k · k : X → [0, ∞) is a function, called a norm, such that (1) kx + yk ≤ kxk + kyk for all x, y ∈ X; (2) kαxk = |α|kxk for all x ∈ X and α ∈ K; (3) kxk = 0 if and only if x = 0. Since kx − yk ≤ kx − zk + kz − yk for all x, y, z ∈ X, d(x, y) = kx − yk defines a metric in a normed space. In what follows normed paces will always be regarded as metric spaces with respect to the metric d. A normed space is called a Banach space if it is complete with respect to the metric d. Definition. Let X be a linear space over K (=R or C). The inner product (scalar product) is a function h·, ·i : X × X → K such that (1) hx, xi ≥ 0; (2) hx, xi = 0 if and only if x = 0; (3) hαx, yi = αhx, yi; (4) hx1 + x2, yi = hx1, yi + hx2, yi; (5) hx, yi = hy, xi, for all x, x1, x2, y ∈ X and all α ∈ K. As an obvious corollary we obtain hx, y1 + y2i = hx, y1i + hx, y2i, hx, αyi = αhx, yi , Date: February 12, 2009. 1 2 PIOTR HAJLASZ for all x, y1, y2 ∈ X and α ∈ K. For a space with an inner product we define kxk = phx, xi . Lemma 1.1 (Schwarz inequality).
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												  Functional Analysis Lecture Notes Chapter 3. BanachFUNCTIONAL ANALYSIS LECTURE NOTES CHAPTER 3. BANACH SPACES CHRISTOPHER HEIL 1. Elementary Properties and Examples Notation 1.1. Throughout, F will denote either the real line R or the complex plane C. All vector spaces are assumed to be over the field F. Definition 1.2. Let X be a vector space over the field F. Then a semi-norm on X is a function k · k: X ! R such that (a) kxk ≥ 0 for all x 2 X, (b) kαxk = jαj kxk for all x 2 X and α 2 F, (c) Triangle Inequality: kx + yk ≤ kxk + kyk for all x, y 2 X. A norm on X is a semi-norm which also satisfies: (d) kxk = 0 =) x = 0. A vector space X together with a norm k · k is called a normed linear space, a normed vector space, or simply a normed space. Definition 1.3. Let I be a finite or countable index set (for example, I = f1; : : : ; Ng if finite, or I = N or Z if infinite). Let w : I ! [0; 1). Given a sequence of scalars x = (xi)i2I , set 1=p jx jp w(i)p ; 0 < p < 1; 8 i kxkp;w = > Xi2I <> sup jxij w(i); p = 1; i2I > where these quantities could be infinite.:> Then we set p `w(I) = x = (xi)i2I : kxkp < 1 : n o p p p We call `w(I) a weighted ` space, and often denote it just by `w (especially if I = N). If p p w(i) = 1 for all i, then we simply call this space ` (I) or ` and write k · kp instead of k · kp;w.
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												  The Nonstandard Theory of Topological Vector SpacesTRANSACTIONS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 172, October 1972 THE NONSTANDARDTHEORY OF TOPOLOGICAL VECTOR SPACES BY C. WARD HENSON AND L. C. MOORE, JR. ABSTRACT. In this paper the nonstandard theory of topological vector spaces is developed, with three main objectives: (1) creation of the basic nonstandard concepts and tools; (2) use of these tools to give nonstandard treatments of some major standard theorems ; (3) construction of the nonstandard hull of an arbitrary topological vector space, and the beginning of the study of the class of spaces which tesults. Introduction. Let Ml be a set theoretical structure and let *JR be an enlarge- ment of M. Let (E, 0) be a topological vector space in M. §§1 and 2 of this paper are devoted to the elementary nonstandard theory of (F, 0). In particular, in §1 the concept of 0-finiteness for elements of *E is introduced and the nonstandard hull of (E, 0) (relative to *3R) is defined. §2 introduces the concept of 0-bounded- ness for elements of *E. In §5 the elementary nonstandard theory of locally convex spaces is developed by investigating the mapping in *JK which corresponds to a given pairing. In §§6 and 7 we make use of this theory by providing nonstandard treatments of two aspects of the existing standard theory. In §6, Luxemburg's characterization of the pre-nearstandard elements of *E for a normed space (E, p) is extended to Hausdorff locally convex spaces (E, 8). This characterization is used to prove the theorem of Grothendieck which gives a criterion for the completeness of a Hausdorff locally convex space.
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												  A Study of Optimization in Hilbert SpaceCalifornia State University, San Bernardino CSUSB ScholarWorks Theses Digitization Project John M. Pfau Library 1998 A study of optimization in Hilbert Space John Awunganyi Follow this and additional works at: https://scholarworks.lib.csusb.edu/etd-project Part of the Mathematics Commons Recommended Citation Awunganyi, John, "A study of optimization in Hilbert Space" (1998). Theses Digitization Project. 1459. https://scholarworks.lib.csusb.edu/etd-project/1459 This Project is brought to you for free and open access by the John M. Pfau Library at CSUSB ScholarWorks. It has been accepted for inclusion in Theses Digitization Project by an authorized administrator of CSUSB ScholarWorks. For more information, please contact [email protected]. A STUDY OF OPTIMIZATIONIN HELBERT SPACE A Project Presented to the Faculty of California State University, San Bernardino In Partial Fulfillment ofthe Requirements for the Degree Master ofArts in Mathematics by John Awunganyi June 1998 A STUDY OF OPTIMIZATION IN HILBERT SPACE A Project Presented to the Faculty of California State University, San Bernardino by John Awunganyi June 1998 Approved by; Dr. Chetan Prakash, Chair, Mathematics Date r. Wenxang Wang Dr. Christopher Freiling Dr. Terry Hallett, Graduate Coordinator Dr. Peter Williams, Department Chair ABSTRACT The primary objective ofthis project is to demonstrate that a certain field ofoptimization can be effectively unified by afew geometric principles ofcomplete normed linear space theory. By employing these principles, important and complex finite - dimensional problems can be interpreted and solved by methods springing from geometric insight. Concepts such as distance, orthogonality, and convexity play a fundamental and indispensable role in this development. Viewed in these terms, seemingly diverse problems and techniques often are found to be closely related.
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												  Eberlein-Šmulian Theorem and Some of Its ApplicationsEberlein-Šmulian theorem and some of its applications Kristina Qarri Supervisors Trond Abrahamsen Associate professor, PhD University of Agder Norway Olav Nygaard Professor, PhD University of Agder Norway This master’s thesis is carried out as a part of the education at the University of Agder and is therefore approved as a part of this education. However, this does not imply that the University answers for the methods that are used or the conclusions that are drawn. University of Agder, 2014 Faculty of Engineering and Science Department of Mathematics Contents Abstract 1 1 Introduction 2 1.1 Notation and terminology . 4 1.2 Cornerstones in Functional Analysis . 4 2 Basics of weak and weak* topologies 6 2.1 The weak topology . 7 2.2 Weak* topology . 16 3 Schauder Basis Theory 21 3.1 First Properties . 21 3.2 Constructing basic sequences . 37 4 Proof of the Eberlein Šmulian theorem due to Whitley 50 5 The weak topology and the topology of pointwise convergence on C(K) 58 6 A generalization of the Ebrlein-Šmulian theorem 64 7 Some applications to Tauberian operator theory 69 Summary 73 i Abstract The thesis is about Eberlein-Šmulian and some its applications. The goal is to investigate and explain different proofs of the Eberlein-Šmulian theorem. First we introduce the general theory of weak and weak* topology defined on a normed space X. Next we present the definition of a basis and a Schauder basis of a given Banach space. We give some examples and prove the main theorems which are needed to enjoy the proof of the Eberlein-Šmulian theorem given by Pelchynski in 1964.
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												  A Hilbert Space Theory of Generalized Graph Signal Processing1 A Hilbert Space Theory of Generalized Graph Signal Processing Feng Ji and Wee Peng Tay, Senior Member, IEEE Abstract Graph signal processing (GSP) has become an important tool in many areas such as image pro- cessing, networking learning and analysis of social network data. In this paper, we propose a broader framework that not only encompasses traditional GSP as a special case, but also includes a hybrid framework of graph and classical signal processing over a continuous domain. Our framework relies extensively on concepts and tools from functional analysis to generalize traditional GSP to graph signals in a separable Hilbert space with infinite dimensions. We develop a concept analogous to Fourier transform for generalized GSP and the theory of filtering and sampling such signals. Index Terms Graph signal proceesing, Hilbert space, generalized graph signals, F-transform, filtering, sampling I. INTRODUCTION Since its emergence, the theory and applications of graph signal processing (GSP) have rapidly developed (see for example, [1]–[10]). Traditional GSP theory is essentially based on a change of orthonormal basis in a finite dimensional vector space. Suppose G = (V; E) is a weighted, arXiv:1904.11655v2 [eess.SP] 16 Sep 2019 undirected graph with V the vertex set of size n and E the set of edges. Recall that a graph signal f assigns a complex number to each vertex, and hence f can be regarded as an element of n C , where C is the set of complex numbers. The heart of the theory is a shift operator AG that is usually defined using a property of the graph.
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												![Arxiv:2003.03538V1 [Math.FA] 7 Mar 2020 Ooois Otniy Discontinuity](https://docslib.b-cdn.net/cover/8028/arxiv-2003-03538v1-math-fa-7-mar-2020-ooois-otniy-discontinuity-768028.webp)  Arxiv:2003.03538V1 [Math.FA] 7 Mar 2020 Ooois Otniy DiscontinuityCONTINUITY AND DISCONTINUITY OF SEMINORMS ON INFINITE-DIMENSIONAL VECTOR SPACES. II JACEK CHMIELINSKI´ Department of Mathematics, Pedagogical University of Krak´ow Krak´ow, Poland E-mail: [email protected] MOSHE GOLDBERG1 Department of Mathematics, Technion – Israel Institute of Technology Haifa, Israel E-mail: [email protected] Abstract. In this paper we extend our findings in [3] and answer further questions regard- ing continuity and discontinuity of seminorms on infinite-dimensional vector spaces. Throughout this paper let X be a vector space over a field F, either R or C. As usual, a real-valued function N : X → R is a norm on X if for all x, y ∈ X and α ∈ F, N(x) > 0, x =06 , N(αx)= |α|N(x), N(x + y) ≤ N(x)+ N(y). Furthermore, a real-valued function S : X → R is called a seminorm if for all x, y ∈ X and α ∈ F, arXiv:2003.03538v1 [math.FA] 7 Mar 2020 S(x) ≥ 0, S(αx)= |α|S(x), S(x + y) ≤ S(x)+ S(y); hence, a norm is a positive-definite seminorm. Using standard terminology, we say that a seminorm S is proper if S does not vanish identically and S(x) = 0 for some x =6 0 or, in other words, if ker S := {x ∈ X : S(x)=0}, is a nontrivial proper subspace of X. 2010 Mathematics Subject Classification. 15A03, 47A30, 54A10, 54C05. Key words and phrases. infinite-dimensional vector spaces, Banach spaces, seminorms, norms, norm- topologies, continuity, discontinuity. 1Corresponding author. 1 2 JACEK CHMIELINSKI´ AND MOSHE GOLDBERG Lastly, just as for norms, we say that seminorms S1 and S2 are equivalent on X, if there exist positive constants β ≤ γ such that for all x ∈ X, βS1(x) ≤ S2(x) ≤ γS1(x).
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												  HILBERT SPACES in MODELLING of SYSTEMS Jean Claude DutaillyHILBERT SPACES IN MODELLING OF SYSTEMS Jean Claude Dutailly To cite this version: Jean Claude Dutailly. HILBERT SPACES IN MODELLING OF SYSTEMS. 2014. hal-00974251 HAL Id: hal-00974251 https://hal.archives-ouvertes.fr/hal-00974251 Preprint submitted on 5 Apr 2014 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. HILBERT SPACES IN MODELLING OF SYSTEMS Jean Claude Dutailly Paris April 4, 2014 Abstract This paper studies the quantitative models which are used to represent systems, whatever the field (Physics, Economics, Finances,...). We prove that models which meet some very general conditions can be associated to Hilbert vector spaces : the state of the system is then identified with a unique vector. The measure of this state is done through observables, whose properties are studied and we show that they can take only values which are eigen vectors of the observables, and a probability law can be associated to the occurence of these measures. The effect of a change of variables in a model is related to a unitary operator. This leads to general laws for the evolution of systems, and to powerful tools for the study of transitions of phases in a system.