Weak and Weak Convergence
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Duality for Outer $ L^ P \Mu (\Ell^ R) $ Spaces and Relation to Tent Spaces
p r DUALITY FOR OUTER Lµpℓ q SPACES AND RELATION TO TENT SPACES MARCO FRACCAROLI p r Abstract. We prove that the outer Lµpℓ q spaces, introduced by Do and Thiele, are isomorphic to Banach spaces, and we show the expected duality properties between them for 1 ă p ď8, 1 ď r ă8 or p “ r P t1, 8u uniformly in the finite setting. In the case p “ 1, 1 ă r ď8, we exhibit a counterexample to uniformity. We show that in the upper half space setting these properties hold true in the full range 1 ď p,r ď8. These results are obtained via greedy p r decompositions of functions in Lµpℓ q. As a consequence, we establish the p p r equivalence between the classical tent spaces Tr and the outer Lµpℓ q spaces in the upper half space. Finally, we give a full classification of weak and strong type estimates for a class of embedding maps to the upper half space with a fractional scale factor for functions on Rd. 1. Introduction The Lp theory for outer measure spaces discussed in [13] generalizes the classical product, or iteration, of weighted Lp quasi-norms. Since we are mainly interested in positive objects, we assume every function to be nonnegative unless explicitly stated. We first focus on the finite setting. On the Cartesian product X of two finite sets equipped with strictly positive weights pY,µq, pZ,νq, we can define the classical product, or iterated, L8Lr,LpLr spaces for 0 ă p, r ă8 by the quasi-norms 1 r r kfkL8ppY,µq,LrpZ,νqq “ supp νpzqfpy,zq q yPY zÿPZ ´1 r 1 “ suppµpyq ωpy,zqfpy,zq q r , yPY zÿPZ p 1 r r p kfkLpppY,µq,LrpZ,νqq “ p µpyqp νpzqfpy,zq q q , arXiv:2001.05903v1 [math.CA] 16 Jan 2020 yÿPY zÿPZ where we denote by ω “ µ b ν the induced weight on X. -
Fundamentals of Functional Analysis Kluwer Texts in the Mathematical Sciences
Fundamentals of Functional Analysis Kluwer Texts in the Mathematical Sciences VOLUME 12 A Graduate-Level Book Series The titles published in this series are listed at the end of this volume. Fundamentals of Functional Analysis by S. S. Kutateladze Sobolev Institute ofMathematics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Springer-Science+Business Media, B.V. A C.I.P. Catalogue record for this book is available from the Library of Congress ISBN 978-90-481-4661-1 ISBN 978-94-015-8755-6 (eBook) DOI 10.1007/978-94-015-8755-6 Translated from OCHOBbI Ij)YHK~HOHaJIl>HODO aHaJIHsa. J/IS;l\~ 2, ;l\OIIOJIHeHHoe., Sobo1ev Institute of Mathematics, Novosibirsk, © 1995 S. S. Kutate1adze Printed on acid-free paper All Rights Reserved © 1996 Springer Science+Business Media Dordrecht Originally published by Kluwer Academic Publishers in 1996. Softcover reprint of the hardcover 1st edition 1996 No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system, without written permission from the copyright owner. Contents Preface to the English Translation ix Preface to the First Russian Edition x Preface to the Second Russian Edition xii Chapter 1. An Excursion into Set Theory 1.1. Correspondences . 1 1.2. Ordered Sets . 3 1.3. Filters . 6 Exercises . 8 Chapter 2. Vector Spaces 2.1. Spaces and Subspaces ... ......................... 10 2.2. Linear Operators . 12 2.3. Equations in Operators ........................ .. 15 Exercises . 18 Chapter 3. Convex Analysis 3.1. -
ON SEQUENCE SPACES DEFINED by the DOMAIN of TRIBONACCI MATRIX in C0 and C Taja Yaying and Merve ˙Ilkhan Kara 1. Introduction Th
Korean J. Math. 29 (2021), No. 1, pp. 25{40 http://dx.doi.org/10.11568/kjm.2021.29.1.25 ON SEQUENCE SPACES DEFINED BY THE DOMAIN OF TRIBONACCI MATRIX IN c0 AND c Taja Yaying∗;y and Merve Ilkhan_ Kara Abstract. In this article we introduce tribonacci sequence spaces c0(T ) and c(T ) derived by the domain of a newly defined regular tribonacci matrix T: We give some topological properties, inclusion relations, obtain the Schauder basis and determine α−; β− and γ− duals of the spaces c0(T ) and c(T ): We characterize certain matrix classes (c0(T );Y ) and (c(T );Y ); where Y is any of the spaces c0; c or `1: Finally, using Hausdorff measure of non-compactness we characterize certain class of compact operators on the space c0(T ): 1. Introduction Throughout the paper N = f0; 1; 2; 3;:::g and w is the space of all real valued sequences. By `1; c0 and c; we mean the spaces all bounded, null and convergent sequences, respectively. Also by `p; cs; cs0 and bs; we mean the spaces of absolutely p-summable, convergent, null and bounded series, respectively, where 1 ≤ p < 1: We write φ for the space of all sequences that terminate in zero. Moreover, we denote the space of all sequences of bounded variation by bv: A Banach space X is said to be a BK-space if it has continuous coordinates. The spaces `1; c0 and c are BK- spaces with norm kxk = sup jx j : Here and henceforth, for simplicity in notation, `1 k k the summation without limit runs from 0 to 1: Also, we shall use the notation e = (1; 1; 1;:::) and e(k) to be the sequence whose only non-zero term is 1 in the kth place for each k 2 N: Let X and Y be two sequence spaces and let A = (ank) be an infinite matrix of real th entries. -
Weak Topologies
Weak topologies David Lecomte May 23, 2006 1 Preliminaries from general topology In this section, we are given a set X, a collection of topological spaces (Yi)i∈I and a collection of maps (fi)i∈I such that each fi maps X into Yi. We wish to define a topology on X that makes all the fi’s continuous. And we want to do this in the cheapest way, that is: there should be no more open sets in X than required for this purpose. −1 Obviously, all the fi (Oi), where Oi is an open set in Yi should be open in X. Then finite intersections of those should also be open. And then any union of finite intersections should be open. By this process, we have created as few open sets as required. Yet it is not clear that the collection obtained is closed under finite intersections. It actually is, as a consequence of the following lemma: Lemma 1 Let X be a set and let O ⊂ P(X) be a collection of subsets of X, such that • ∅ and X are in O; • O is closed under finite intersections. Then T = { O | O ⊂ O} is a topology on X. OS∈O Proof: By definition, T contains X and ∅ since those were already in O. Furthermore, T is closed under unions, again by definition. So all that’s left is to check that T is closed under finite intersections. Let A1 and A2 be two elements of T . Then there exist O1 and O2, subsets of O, such that A = O and A = O 1 [ 2 [ O∈O1 O∈O2 1 It is then easy to check by double inclusion that A ∩ A = O ∩ O 1 2 [ 1 2 O1∈O1 O2∈O2 Letting O denote the collection {O1 ∩ O2 | O1 ∈ O1 O2 ∈ O2}, which is a subset of O since the latter is closed under finite intersections, we get A ∩ A = O 1 2 [ O∈O This set belongs to T . -
Distinguished Property in Tensor Products and Weak* Dual Spaces
axioms Article Distinguished Property in Tensor Products and Weak* Dual Spaces Salvador López-Alfonso 1 , Manuel López-Pellicer 2,* and Santiago Moll-López 3 1 Department of Architectural Constructions, Universitat Politècnica de València, 46022 Valencia, Spain; [email protected] 2 Emeritus and IUMPA, Universitat Politècnica de València, 46022 Valencia, Spain 3 Department of Applied Mathematics, Universitat Politècnica de València, 46022 Valencia, Spain; [email protected] * Correspondence: [email protected] 0 Abstract: A local convex space E is said to be distinguished if its strong dual Eb has the topology 0 0 0 0 b(E , (Eb) ), i.e., if Eb is barrelled. The distinguished property of the local convex space Cp(X) of real- valued functions on a Tychonoff space X, equipped with the pointwise topology on X, has recently aroused great interest among analysts and Cp-theorists, obtaining very interesting properties and nice characterizations. For instance, it has recently been obtained that a space Cp(X) is distinguished if and only if any function f 2 RX belongs to the pointwise closure of a pointwise bounded set in C(X). The extensively studied distinguished properties in the injective tensor products Cp(X) ⊗# E and in Cp(X, E) contrasts with the few distinguished properties of injective tensor products related to the dual space Lp(X) of Cp(X) endowed with the weak* topology, as well as to the weak* dual of Cp(X, E). To partially fill this gap, some distinguished properties in the injective tensor product space Lp(X) ⊗# E are presented and a characterization of the distinguished property of the weak* dual of Cp(X, E) for wide classes of spaces X and E is provided. -
Sequential Completeness of Inductive Limits
Internat. J. Math. & Math. Sci. Vol. 24, No. 6 (2000) 419–421 S0161171200003744 © Hindawi Publishing Corp. SEQUENTIAL COMPLETENESS OF INDUCTIVE LIMITS CLAUDIA GÓMEZ and JAN KUCERAˇ (Received 28 July 1999) Abstract. A regular inductive limit of sequentially complete spaces is sequentially com- plete. For the converse of this theorem we have a weaker result: if indEn is sequentially complete inductive limit, and each constituent space En is closed in indEn, then indEn is α-regular. Keywords and phrases. Regularity, α-regularity, sequential completeness of locally convex inductive limits. 2000 Mathematics Subject Classification. Primary 46A13; Secondary 46A30. 1. Introduction. In [2] Kuˇcera proves that an LF-space is regular if and only if it is sequentially complete. In [1] Bosch and Kuˇcera prove the equivalence of regularity and sequential completeness for bornivorously webbed spaces. It is natural to ask: can this result be extended to arbitrary sequentially complete spaces? We give a partial answer to this question in this paper. 2. Definitions. Throughout the paper {(En,τn)}n∈N is an increasing sequence of Hausdorff locally convex spaces with continuous identity maps id : En → En+1 and E = indEn its inductive limit. A topological vector space E is sequentially complete if every Cauchy sequence {xn}⊂E is convergent to an element x ∈ E. An inductive limit indEn is regular, resp. α-regular, if each of its bounded sets is bounded, resp. contained, in some constituent space En. 3. Main results Theorem 3.1. Let each space (En,τn) be sequentially complete and indEn regular. Then indEn is sequentially complete. Proof. Let {xk} be a Cauchy sequence in indEn. -
Chapter 4 the Lebesgue Spaces
Chapter 4 The Lebesgue Spaces In this chapter we study Lp-integrable functions as a function space. Knowledge on functional analysis required for our study is briefly reviewed in the first two sections. In Section 1 the notions of normed and inner product spaces and their properties such as completeness, separability, the Heine-Borel property and espe- cially the so-called projection property are discussed. Section 2 is concerned with bounded linear functionals and the dual space of a normed space. The Lp-space is introduced in Section 3, where its completeness and various density assertions by simple or continuous functions are covered. The dual space of the Lp-space is determined in Section 4 where the key notion of uniform convexity is introduced and established for the Lp-spaces. Finally, we study strong and weak conver- gence of Lp-sequences respectively in Sections 5 and 6. Both are important for applications. 4.1 Normed Spaces In this and the next section we review essential elements of functional analysis that are relevant to our study of the Lp-spaces. You may look up any book on functional analysis or my notes on this subject attached in this webpage. Let X be a vector space over R. A norm on X is a map from X ! [0; 1) satisfying the following three \axioms": For 8x; y; z 2 X, (i) kxk ≥ 0 and is equal to 0 if and only if x = 0; (ii) kαxk = jαj kxk, 8α 2 R; and (iii) kx + yk ≤ kxk + kyk. The pair (X; k·k) is called a normed vector space or normed space for short. -
FUNCTIONAL ANALYSIS 1. Banach and Hilbert Spaces in What
FUNCTIONAL 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). -
View of This, the Following Observation Should Be of Some Interest to Vector Space Pathologists
Can. J. Math., Vol. XXV, No. 3, 1973, pp. 511-524 INCLUSION THEOREMS FOR Z-SPACES G. BENNETT AND N. J. KALTON 1. Notation and preliminary ideas. A sequence space is a vector subspace of the space co of all real (or complex) sequences. A sequence space E with a locally convex topology r is called a K- space if the inclusion map E —* co is continuous, when co is endowed with the product topology (co = II^Li (R)*). A i£-space E with a Frechet (i.e., complete, metrizable and locally convex) topology is called an FK-space; if the topology is a Banach topology, then E is called a BK-space. The following familiar BK-spaces will be important in the sequel: ni, the space of all bounded sequences; c, the space of all convergent sequences; Co, the space of all null sequences; lp, 1 ^ p < °°, the space of all absolutely ^-summable sequences. We shall also consider the space <j> of all finite sequences and the linear span, Wo, of all sequences of zeros and ones; these provide examples of spaces having no FK-topology. A sequence space is solid (respectively monotone) provided that xy £ E whenever x 6 m (respectively m0) and y £ E. For x £ co, we denote by Pn(x) the sequence (xi, x2, . xn, 0, . .) ; if a i£-space (E, r) has the property that Pn(x) —» x in r for each x G E, then we say that (£, r) is an AK-space. We also write WE = \x Ç £: P„.(x) —>x weakly} and ^ = jx Ç E: Pn{x) —>x in r}. -
Functional Analysis Lecture Notes Chapter 3. Banach
FUNCTIONAL 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. -
The Nonstandard Theory of Topological Vector Spaces
TRANSACTIONS 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. -
Functional Analysis Lecture Notes Chapter 2. Operators on Hilbert Spaces
FUNCTIONAL ANALYSIS LECTURE NOTES CHAPTER 2. OPERATORS ON HILBERT SPACES CHRISTOPHER HEIL 1. Elementary Properties and Examples First recall the basic definitions regarding operators. Definition 1.1 (Continuous and Bounded Operators). Let X, Y be normed linear spaces, and let L: X Y be a linear operator. ! (a) L is continuous at a point f X if f f in X implies Lf Lf in Y . 2 n ! n ! (b) L is continuous if it is continuous at every point, i.e., if fn f in X implies Lfn Lf in Y for every f. ! ! (c) L is bounded if there exists a finite K 0 such that ≥ f X; Lf K f : 8 2 k k ≤ k k Note that Lf is the norm of Lf in Y , while f is the norm of f in X. k k k k (d) The operator norm of L is L = sup Lf : k k kfk=1 k k (e) We let (X; Y ) denote the set of all bounded linear operators mapping X into Y , i.e., B (X; Y ) = L: X Y : L is bounded and linear : B f ! g If X = Y = X then we write (X) = (X; X). B B (f) If Y = F then we say that L is a functional. The set of all bounded linear functionals on X is the dual space of X, and is denoted X0 = (X; F) = L: X F : L is bounded and linear : B f ! g We saw in Chapter 1 that, for a linear operator, boundedness and continuity are equivalent.