Generalized Vectorial Lebesgue and Bochner Integration Theory
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2.1 the Algebra of Sets
Chapter 2 I Abstract Algebra 83 part of abstract algebra, sets are fundamental to all areas of mathematics and we need to establish a precise language for sets. We also explore operations on sets and relations between sets, developing an “algebra of sets” that strongly resembles aspects of the algebra of sentential logic. In addition, as we discussed in chapter 1, a fundamental goal in mathematics is crafting articulate, thorough, convincing, and insightful arguments for the truth of mathematical statements. We continue the development of theorem-proving and proof-writing skills in the context of basic set theory. After exploring the algebra of sets, we study two number systems denoted Zn and U(n) that are closely related to the integers. Our approach is based on a widely used strategy of mathematicians: we work with specific examples and look for general patterns. This study leads to the definition of modified addition and multiplication operations on certain finite subsets of the integers. We isolate key axioms, or properties, that are satisfied by these and many other number systems and then examine number systems that share the “group” properties of the integers. Finally, we consider an application of this mathematics to check digit schemes, which have become increasingly important for the success of business and telecommunications in our technologically based society. Through the study of these topics, we engage in a thorough introduction to abstract algebra from the perspective of the mathematician— working with specific examples to identify key abstract properties common to diverse and interesting mathematical systems. 2.1 The Algebra of Sets Intuitively, a set is a “collection” of objects known as “elements.” But in the early 1900’s, a radical transformation occurred in mathematicians’ understanding of sets when the British philosopher Bertrand Russell identified a fundamental paradox inherent in this intuitive notion of a set (this paradox is discussed in exercises 66–70 at the end of this section). -
1 Sets and Classes
Prerequisites Topological spaces. A set E in a space X is σ-compact if there exists a S1 sequence of compact sets such that E = n=1 Cn. A space X is locally compact if every point of X has a neighborhood whose closure is compact. A subset E of a locally compact space is bounded if there exists a compact set C such that E ⊂ C. Topological groups. The set xE [or Ex] is called a left translation [or right translation.] If Y is a subgroup of X, the sets xY and Y x are called (left and right) cosets of Y . A topological group is a group X which is a Hausdorff space such that the transformation (from X ×X onto X) which sends (x; y) into x−1y is continuous. A class N of open sets containing e in a topological group is a base at e if (a) for every x different form e there exists a set U in N such that x2 = U, (b) for any two sets U and V in N there exists a set W in N such that W ⊂ U \ V , (c) for any set U 2 N there exists a set W 2 N such that V −1V ⊂ U, (d) for any set U 2 N and any element x 2 X, there exists a set V 2 N such that V ⊂ xUx−1, and (e) for any set U 2 N there exists a set V 2 N such that V x ⊂ U. If N is a satisfies the conditions described above, and if the class of all translation of sets of N is taken for a base, then, with respect to the topology so defined, X becomes a topological group. -
Arxiv:1910.08491V3 [Math.ST] 3 Nov 2020
Weakly stationary stochastic processes valued in a separable Hilbert space: Gramian-Cram´er representations and applications Amaury Durand ∗† Fran¸cois Roueff ∗ September 14, 2021 Abstract The spectral theory for weakly stationary processes valued in a separable Hilbert space has known renewed interest in the past decade. However, the recent literature on this topic is often based on restrictive assumptions or lacks important insights. In this paper, we follow earlier approaches which fully exploit the normal Hilbert module property of the space of Hilbert- valued random variables. This approach clarifies and completes the isomorphic relationship between the modular spectral domain to the modular time domain provided by the Gramian- Cram´er representation. We also discuss the general Bochner theorem and provide useful results on the composition and inversion of lag-invariant linear filters. Finally, we derive the Cram´er-Karhunen-Lo`eve decomposition and harmonic functional principal component analysis without relying on simplifying assumptions. 1 Introduction Functional data analysis has become an active field of research in the recent decades due to technological advances which makes it possible to store longitudinal data at very high frequency (see e.g. [22, 31]), or complex data e.g. in medical imaging [18, Chapter 9], [15], linguistics [28] or biophysics [27]. In these frameworks, the data is seen as valued in an infinite dimensional separable Hilbert space thus isomorphic to, and often taken to be, the function space L2(0, 1) of Lebesgue-square-integrable functions on [0, 1]. In this setting, a 2 functional time series refers to a bi-sequences (Xt)t∈Z of L (0, 1)-valued random variables and the assumption of finite second moment means that each random variable Xt belongs to the L2 Bochner space L2(Ω, F, L2(0, 1), P) of measurable mappings V : Ω → L2(0, 1) such that E 2 kV kL2(0,1) < ∞ , where k·kL2(0,1) here denotes the norm endowing the Hilbert space L2h(0, 1). -
A. the Bochner Integral
A. The Bochner Integral This chapter is a slight modification of Chap. A in [FK01]. Let X, be a Banach space, B(X) the Borel σ-field of X and (Ω, F,µ) a measure space with finite measure µ. A.1. Definition of the Bochner integral Step 1: As first step we want to define the integral for simple functions which are defined as follows. Set n E → ∈ ∈F ∈ N := f :Ω X f = xk1Ak ,xk X, Ak , 1 k n, n k=1 and define a semi-norm E on the vector space E by f E := f dµ, f ∈E. To get that E, E is a normed vector space we consider equivalence classes with respect to E . For simplicity we will not change the notations. ∈E n For f , f = k=1 xk1Ak , Ak’s pairwise disjoint (such a representation n is called normal and always exists, because f = k=1 xk1Ak , where f(Ω) = {x1,...,xk}, xi = xj,andAk := {f = xk}) and we now define the Bochner integral to be n f dµ := xkµ(Ak). k=1 (Exercise: This definition is independent of representations, and hence linear.) In this way we get a mapping E → int : , E X, f → f dµ which is linear and uniformly continuous since f dµ f dµ for all f ∈E. Therefore we can extend the mapping int to the abstract completion of E with respect to E which we denote by E. 105 106 A. The Bochner Integral Step 2: We give an explicit representation of E. Definition A.1.1. -
An Elementary Approach to Boolean Algebra
Eastern Illinois University The Keep Plan B Papers Student Theses & Publications 6-1-1961 An Elementary Approach to Boolean Algebra Ruth Queary Follow this and additional works at: https://thekeep.eiu.edu/plan_b Recommended Citation Queary, Ruth, "An Elementary Approach to Boolean Algebra" (1961). Plan B Papers. 142. https://thekeep.eiu.edu/plan_b/142 This Dissertation/Thesis is brought to you for free and open access by the Student Theses & Publications at The Keep. It has been accepted for inclusion in Plan B Papers by an authorized administrator of The Keep. For more information, please contact [email protected]. r AN ELEr.:ENTARY APPRCACH TC BCCLF.AN ALGEBRA RUTH QUEAHY L _J AN ELE1~1ENTARY APPRCACH TC BC CLEAN ALGEBRA Submitted to the I<:athematics Department of EASTERN ILLINCIS UNIVERSITY as partial fulfillment for the degree of !•:ASTER CF SCIENCE IN EJUCATION. Date :---"'f~~-----/_,_ffo--..i.-/ _ RUTH QUEARY JUNE 1961 PURPOSE AND PLAN The purpose of this paper is to provide an elementary approach to Boolean algebra. It is designed to give an idea of what is meant by a Boclean algebra and to supply the necessary background material. The only prerequisite for this unit is one year of high school algebra and an open mind so that new concepts will be considered reason able even though they nay conflict with preconceived ideas. A mathematical science when put in final form consists of a set of undefined terms and unproved propositions called postulates, in terrrs of which all other concepts are defined, and from which all other propositions are proved. -
On Families of Mutually Exclusive Sets
ANNALS OF MATHEMATICS Vol. 44, No . 2, April, 1943 ON FAMILIES OF MUTUALLY EXCLUSIVE SETS BY P . ERDÖS AND A. TARSKI (Received August 11, 1942) In this paper we shall be concerned with a certain particular problem from the general theory of sets, namely with the problem of the existence of families of mutually exclusive sets with a maximal power . It will turn out-in a rather unexpected way that the solution of these problems essentially involves the notion of the so-called "inaccessible numbers ." In this connection we shall make some general remarks regarding inaccessible numbers in the last section of our paper . §1. FORMULATION OF THE PROBLEM . TERMINOLOGY' The problem in which we are interested can be stated as follows : Is it true that every field F of sets contains a family of mutually exclusive sets with a maximal power, i .e . a family O whose cardinal number is not smaller than the cardinal number of any other family of mutually exclusive sets contained in F . By a field of sets we understand here as usual a family F of sets which to- gether with every two sets X and Y contains also their union X U Y and their difference X - Y (i.e. the set of those elements of X which do not belong to Y) among its elements . A family O is called a family of mutually exclusive sets if no set X of X of O is empty and if any two different sets of O have an empty inter- section. A similar problem can be formulated for other families e .g . -
Completely Representable Lattices
Completely representable lattices Robert Egrot and Robin Hirsch Abstract It is known that a lattice is representable as a ring of sets iff the lattice is distributive. CRL is the class of bounded distributive lattices (DLs) which have representations preserving arbitrary joins and meets. jCRL is the class of DLs which have representations preserving arbitrary joins, mCRL is the class of DLs which have representations preserving arbitrary meets, and biCRL is defined to be jCRL ∩ mCRL. We prove CRL ⊂ biCRL = mCRL ∩ jCRL ⊂ mCRL =6 jCRL ⊂ DL where the marked inclusions are proper. Let L be a DL. Then L ∈ mCRL iff L has a distinguishing set of complete, prime filters. Similarly, L ∈ jCRL iff L has a distinguishing set of completely prime filters, and L ∈ CRL iff L has a distinguishing set of complete, completely prime filters. Each of the classes above is shown to be pseudo-elementary hence closed under ultraproducts. The class CRL is not closed under elementary equivalence, hence it is not elementary. 1 Introduction An atomic representation h of a Boolean algebra B is a representation h: B → ℘(X) (some set X) where h(1) = {h(a): a is an atom of B}. It is known that a representation of a Boolean algebraS is a complete representation (in the sense of a complete embedding into a field of sets) if and only if it is an atomic repre- sentation and hence that the class of completely representable Boolean algebras is precisely the class of atomic Boolean algebras, and hence is elementary [6]. arXiv:1201.2331v3 [math.RA] 30 Aug 2016 This result is not obvious as the usual definition of a complete representation is thoroughly second order. -
Equivalents to the Axiom of Choice and Their Uses A
EQUIVALENTS TO THE AXIOM OF CHOICE AND THEIR USES A Thesis Presented to The Faculty of the Department of Mathematics California State University, Los Angeles In Partial Fulfillment of the Requirements for the Degree Master of Science in Mathematics By James Szufu Yang c 2015 James Szufu Yang ALL RIGHTS RESERVED ii The thesis of James Szufu Yang is approved. Mike Krebs, Ph.D. Kristin Webster, Ph.D. Michael Hoffman, Ph.D., Committee Chair Grant Fraser, Ph.D., Department Chair California State University, Los Angeles June 2015 iii ABSTRACT Equivalents to the Axiom of Choice and Their Uses By James Szufu Yang In set theory, the Axiom of Choice (AC) was formulated in 1904 by Ernst Zermelo. It is an addition to the older Zermelo-Fraenkel (ZF) set theory. We call it Zermelo-Fraenkel set theory with the Axiom of Choice and abbreviate it as ZFC. This paper starts with an introduction to the foundations of ZFC set the- ory, which includes the Zermelo-Fraenkel axioms, partially ordered sets (posets), the Cartesian product, the Axiom of Choice, and their related proofs. It then intro- duces several equivalent forms of the Axiom of Choice and proves that they are all equivalent. In the end, equivalents to the Axiom of Choice are used to prove a few fundamental theorems in set theory, linear analysis, and abstract algebra. This paper is concluded by a brief review of the work in it, followed by a few points of interest for further study in mathematics and/or set theory. iv ACKNOWLEDGMENTS Between the two department requirements to complete a master's degree in mathematics − the comprehensive exams and a thesis, I really wanted to experience doing a research and writing a serious academic paper. -
Section 17.5. the Carathéodry-Hahn Theorem: the Extension of A
17.5. The Carath´eodory-Hahn Theorem 1 Section 17.5. The Carath´eodry-Hahn Theorem: The Extension of a Premeasure to a Measure Note. We have µ defined on S and use µ to define µ∗ on X. We then restrict µ∗ to a subset of X on which µ∗ is a measure (denoted µ). Unlike with Lebesgue measure where the elements of S are measurable sets themselves (and S is the set of open intervals), we may not have µ defined on S. In this section, we look for conditions on µ : S → [0, ∞] which imply the measurability of the elements of S. Under these conditions, µ is then an extension of µ from S to M (the σ-algebra of measurable sets). ∞ Definition. A set function µ : S → [0, ∞] is finitely additive if whenever {Ek}k=1 ∞ is a finite disjoint collection of sets in S and ∪k=1Ek ∈ S, we have n n µ · Ek = µ(Ek). k=1 ! k=1 [ X Note. We have previously defined finitely monotone for set functions and Propo- sition 17.6 gives finite additivity for an outer measure on M, but this is the first time we have discussed a finitely additive set function. Proposition 17.11. Let S be a collection of subsets of X and µ : S → [0, ∞] a set function. In order that the Carath´eodory measure µ induced by µ be an extension of µ (that is, µ = µ on S) it is necessary that µ be both finitely additive and countably monotone and, if ∅ ∈ S, then µ(∅) = 0. -
Bochner Integrals and Vector Measures
Michigan Technological University Digital Commons @ Michigan Tech Dissertations, Master's Theses and Master's Reports 1993 Bochner Integrals and Vector Measures Ivaylo D. Dinov Michigan Technological University Copyright 1993 Ivaylo D. Dinov Recommended Citation Dinov, Ivaylo D., "Bochner Integrals and Vector Measures", Open Access Master's Report, Michigan Technological University, 1993. https://doi.org/10.37099/mtu.dc.etdr/919 Follow this and additional works at: https://digitalcommons.mtu.edu/etdr Part of the Mathematics Commons “BOCHNER INTEGRALS AND VECTOR MEASURES” Project for the Degree of M.S. MICHIGAN TECH UNIVERSITY IVAYLO D. DINOV BOCHNER INTEGRALS RND VECTOR MEASURES By IVAYLO D. DINOV A REPORT (PROJECT) Submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE IN MATHEMATICS Spring 1993 MICHIGAN TECHNOLOGICRL UNIUERSITV HOUGHTON, MICHIGAN U.S.R. 4 9 9 3 1 -1 2 9 5 . Received J. ROBERT VAN PELT LIBRARY APR 2 0 1993 MICHIGAN TECHNOLOGICAL UNIVERSITY I HOUGHTON, MICHIGAN GRADUATE SCHOOL MICHIGAN TECH This Project, “Bochner Integrals and Vector Measures”, is hereby approved in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE IN MATHEMATICS. DEPARTMENT OF MATHEMATICAL SCIENCES MICHIGAN TECHNOLOGICAL UNIVERSITY Project A d v is o r Kenneth L. Kuttler Head of Department— Dr.Alphonse Baartmans 2o April 1992 Date •vaylo D. Dinov “Bochner Integrals and Vector Measures” 1400 TOWNSEND DRIVE. HOUGHTON Ml 49931-1295 flskngiyledgtiients I wish to express my appreciation to my advisor, Dr. Kenneth L. Kuttler, for his help, guidance and direction in the preparation of this report. The corrections and the revisions that he suggested made the project look complete and easy to read. -
BOCHNER Vs. PETTIS NORM: EXAMPLES and RESULTS 3
Contemp orary Mathematics Volume 00, 0000 Bo chner vs. Pettis norm: examples and results S.J. DILWORTH AND MARIA GIRARDI Contemp. Math. 144 1993 69{80 Banach Spaces, Bor-Luh Lin and Wil liam B. Johnson, editors Abstract. Our basic example shows that for an arbitrary in nite-dimen- sional Banach space X, the Bo chner norm and the Pettis norm on L X are 1 not equivalent. Re nements of this example are then used to investigate various mo des of sequential convergence in L X. 1 1. INTRODUCTION Over the years, the Pettis integral along with the Pettis norm have grabb ed the interest of many. In this note, we wish to clarify the di erences b etween the Bo chner and the Pettis norms. We b egin our investigation by using Dvoretzky's Theorem to construct, for an arbitrary in nite-dimensional Banach space, a se- quence of Bo chner integrable functions whose Bo chner norms tend to in nity but whose Pettis norms tend to zero. By re ning this example again working with an arbitrary in nite-dimensional Banach space, we pro duce a Pettis integrable function that is not Bo chner integrable and we show that the space of Pettis integrable functions is not complete. Thus our basic example provides a uni- ed constructiveway of seeing several known facts. The third section expresses these results from a vector measure viewp oint. In the last section, with the aid of these examples, we give a fairly thorough survey of the implications going between various mo des of convergence for sequences of L X functions. -
Sets, Functions, Relations
Mathematics for Computer Scientists Lecture notes for the module G51MCS Venanzio Capretta University of Nottingham School of Computer Science Chapter 4 Sets, Functions and Relations 4.1 Sets Sets are such a basic notion in mathematics that the only way to ‘define’ them is by synonyms like collection, class, grouping and so on. A set is completely characterised by the elements it contains. There are two main ways of defining a set: (1) by explicitly listing all its elements or (2) by giving a property that all elements must satisfy. Here is a couple of examples, the first is a set of fruits given by listing its elements, the second is a set of natural numbers given by specifying a property: A = {apple, banana, cherry, peach} E = {n ∈ N | 2 divides n} The definition of E can be read: E is the set of those natural numbers that are divisible by 2, that is, it’s the set of all even naturals. The first definition method can be used only if the set has a finite number of elements. In some cases both methods can be used to define the same set, as in this example: 2 {n ∈ N | n is odd ∧ n + n ≤ 100} = {1, 3, 5, 7, 9} To say that a certain object x is an element of a set S, we write x ∈ S. To say that it isn’t an element of S we write x 6∈ S. For example: apple ∈ A 7 6∈ E strawberry 6∈ A 8 ∈ E If every element of a set X is also an element of another set Y , then we say that X is a subset of Y and we write this symbolically as X ⊆ Y .