Difference and Symmetric Difference Operations Defined on Intuitionistic Fuzzy Multisets
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A Class of Symmetric Difference-Closed Sets Related to Commuting Involutions John Campbell
A class of symmetric difference-closed sets related to commuting involutions John Campbell To cite this version: John Campbell. A class of symmetric difference-closed sets related to commuting involutions. Discrete Mathematics and Theoretical Computer Science, DMTCS, 2017, Vol 19 no. 1. hal-01345066v4 HAL Id: hal-01345066 https://hal.archives-ouvertes.fr/hal-01345066v4 Submitted on 18 Mar 2017 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. Discrete Mathematics and Theoretical Computer Science DMTCS vol. 19:1, 2017, #8 A class of symmetric difference-closed sets related to commuting involutions John M. Campbell York University, Canada received 19th July 2016, revised 15th Dec. 2016, 1st Feb. 2017, accepted 10th Feb. 2017. Recent research on the combinatorics of finite sets has explored the structure of symmetric difference-closed sets, and recent research in combinatorial group theory has concerned the enumeration of commuting involutions in Sn and An. In this article, we consider an interesting combination of these two subjects, by introducing classes of symmetric difference-closed sets of elements which correspond in a natural way to commuting involutions in Sn and An. We consider the natural combinatorial problem of enumerating symmetric difference-closed sets consisting of subsets of sets consisting of pairwise disjoint 2-subsets of [n], and the problem of enumerating symmetric difference-closed sets consisting of elements which correspond to commuting involutions in An. -
TOPOLOGY and ITS APPLICATIONS the Number of Complements in The
TOPOLOGY AND ITS APPLICATIONS ELSEVIER Topology and its Applications 55 (1994) 101-125 The number of complements in the lattice of topologies on a fixed set Stephen Watson Department of Mathematics, York Uniuersity, 4700 Keele Street, North York, Ont., Canada M3J IP3 (Received 3 May 1989) (Revised 14 November 1989 and 2 June 1992) Abstract In 1936, Birkhoff ordered the family of all topologies on a set by inclusion and obtained a lattice with 1 and 0. The study of this lattice ought to be a basic pursuit both in combinatorial set theory and in general topology. In this paper, we study the nature of complementation in this lattice. We say that topologies 7 and (T are complementary if and only if 7 A c = 0 and 7 V (T = 1. For simplicity, we call any topology other than the discrete and the indiscrete a proper topology. Hartmanis showed in 1958 that any proper topology on a finite set of size at least 3 has at least two complements. Gaifman showed in 1961 that any proper topology on a countable set has at least two complements. In 1965, Steiner showed that any topology has a complement. The question of the number of distinct complements a topology on a set must possess was first raised by Berri in 1964 who asked if every proper topology on an infinite set must have at least two complements. In 1969, Schnare showed that any proper topology on a set of infinite cardinality K has at least K distinct complements and at most 2” many distinct complements. -
Determinacy in Linear Rational Expectations Models
Journal of Mathematical Economics 40 (2004) 815–830 Determinacy in linear rational expectations models Stéphane Gauthier∗ CREST, Laboratoire de Macroéconomie (Timbre J-360), 15 bd Gabriel Péri, 92245 Malakoff Cedex, France Received 15 February 2002; received in revised form 5 June 2003; accepted 17 July 2003 Available online 21 January 2004 Abstract The purpose of this paper is to assess the relevance of rational expectations solutions to the class of linear univariate models where both the number of leads in expectations and the number of lags in predetermined variables are arbitrary. It recommends to rule out all the solutions that would fail to be locally unique, or equivalently, locally determinate. So far, this determinacy criterion has been applied to particular solutions, in general some steady state or periodic cycle. However solutions to linear models with rational expectations typically do not conform to such simple dynamic patterns but express instead the current state of the economic system as a linear difference equation of lagged states. The innovation of this paper is to apply the determinacy criterion to the sets of coefficients of these linear difference equations. Its main result shows that only one set of such coefficients, or the corresponding solution, is locally determinate. This solution is commonly referred to as the fundamental one in the literature. In particular, in the saddle point configuration, it coincides with the saddle stable (pure forward) equilibrium trajectory. © 2004 Published by Elsevier B.V. JEL classification: C32; E32 Keywords: Rational expectations; Selection; Determinacy; Saddle point property 1. Introduction The rational expectations hypothesis is commonly justified by the fact that individual forecasts are based on the relevant theory of the economic system. -
180: Counting Techniques
180: Counting Techniques In the following exercise we demonstrate the use of a few fundamental counting principles, namely the addition, multiplication, complementary, and inclusion-exclusion principles. While none of the principles are particular complicated in their own right, it does take some practice to become familiar with them, and recognise when they are applicable. I have attempted to indicate where alternate approaches are possible (and reasonable). Problem: Assume n ≥ 2 and m ≥ 1. Count the number of functions f :[n] ! [m] (i) in total. (ii) such that f(1) = 1 or f(2) = 1. (iii) with minx2[n] f(x) ≤ 5. (iv) such that f(1) ≥ f(2). (v) that are strictly increasing; that is, whenever x < y, f(x) < f(y). (vi) that are one-to-one (injective). (vii) that are onto (surjective). (viii) that are bijections. (ix) such that f(x) + f(y) is even for every x; y 2 [n]. (x) with maxx2[n] f(x) = minx2[n] f(x) + 1. Solution: (i) A function f :[n] ! [m] assigns for every integer 1 ≤ x ≤ n an integer 1 ≤ f(x) ≤ m. For each integer x, we have m options. As we make n such choices (independently), the total number of functions is m × m × : : : m = mn. (ii) (We assume n ≥ 2.) Let A1 be the set of functions with f(1) = 1, and A2 the set of functions with f(2) = 1. Then A1 [ A2 represents those functions with f(1) = 1 or f(2) = 1, which is precisely what we need to count. We have jA1 [ A2j = jA1j + jA2j − jA1 \ A2j. -
1 Measurable Sets
Math 4351, Fall 2018 Chapter 11 in Goldberg 1 Measurable Sets Our goal is to define what is meant by a measurable set E ⊆ [a; b] ⊂ R and a measurable function f :[a; b] ! R. We defined the length of an open set and a closed set, denoted as jGj and jF j, e.g., j[a; b]j = b − a: We will use another notation for complement and the notation in the Goldberg text. Let Ec = [a; b] n E = [a; b] − E. Also, E1 n E2 = E1 − E2: Definitions: Let E ⊆ [a; b]. Outer measure of a set E: m(E) = inffjGj : for all G open and E ⊆ Gg. Inner measure of a set E: m(E) = supfjF j : for all F closed and F ⊆ Eg: 0 ≤ m(E) ≤ m(E). A set E is a measurable set if m(E) = m(E) and the measure of E is denoted as m(E). The symmetric difference of two sets E1 and E2 is defined as E1∆E2 = (E1 − E2) [ (E2 − E1): A set is called an Fσ set (F-sigma set) if it is a union of a countable number of closed sets. A set is called a Gδ set (G-delta set) if it is a countable intersection of open sets. Properties of Measurable Sets on [a; b]: 1. If E1 and E2 are subsets of [a; b] and E1 ⊆ E2, then m(E1) ≤ m(E2) and m(E1) ≤ m(E2). In addition, if E1 and E2 are measurable subsets of [a; b] and E1 ⊆ E2, then m(E1) ≤ m(E2). -
Set Difference and Symmetric Difference of Fuzzy Sets
Preliminaries Symmetric Dierence Set Dierence and Symmetric Dierence of Fuzzy Sets N.R. Vemuri A.S. Hareesh M.S. Srinath Department of Mathematics Indian Institute of Technology, Hyderabad and Department of Mathematics and Computer Science Sri Sathya Sai Institute of Higher Learning, India Fuzzy Sets Theory and Applications 2014, Liptovský Ján, Slovak Republic Vemuri, Sai Hareesh & Srinath Symmetric Dierence Preliminaries Introduction Symmetric Dierence Earlier work Outline 1 Preliminaries Introduction Earlier work 2 Symmetric Dierence Denition Examples Properties Applications Future Work References Vemuri, Sai Hareesh & Srinath Symmetric Dierence Preliminaries Introduction Symmetric Dierence Earlier work Classical set theory Set operations Union- [ Intersection - \ Complement - c Dierence -n Symmetric dierence - ∆ .... Vemuri, Sai Hareesh & Srinath Symmetric Dierence Preliminaries Introduction Symmetric Dierence Earlier work Classical set theory Set operations Union- [ Intersection - \ Complement - c Dierence -n Symmetric dierence - ∆ .... Vemuri, Sai Hareesh & Srinath Symmetric Dierence Preliminaries Introduction Symmetric Dierence Earlier work Classical set theory Set operations Union- [ Intersection - \ Complement - c Dierence -n Symmetric dierence - ∆ .... Vemuri, Sai Hareesh & Srinath Symmetric Dierence Preliminaries Introduction Symmetric Dierence Earlier work Classical set theory Set operations Union- [ Intersection - \ Complement - c Dierence -n Symmetric dierence - ∆ .... Vemuri, Sai Hareesh & Srinath Symmetric Dierence Preliminaries -
E. A. Emerson and C. S. Jutla, Tree Automata, Mu-Calculus, And
Tree Automata MuCalculus and Determinacy Extended Abstract EA Emerson and CS Jutla The University of Texas at Austin IBM TJ Watson Research Center Abstract that tree automata are closed under disjunction pro jection and complementation While the rst two We show that the prop ositional MuCalculus is eq are rather easy the pro of of Rabins Complemen uivalent in expressivepower to nite automata on in tation Lemma is extraordinarily complex and di nite trees Since complementation is trivial in the Mu cult Because of the imp ortance of the Complemen Calculus our equivalence provides a radically sim tation Lemma a numb er of authors have endeavored plied alternative pro of of Rabins complementation and continue to endeavor to simplify the argument lemma for tree automata which is the heart of one HR GH MS Mu Perhaps the b est of the deep est decidability results We also showhow known of these is the imp ortant work of Gurevich MuCalculus can b e used to establish determinacy of and Harrington GH which attacks the problem innite games used in earlier pro ofs of complementa from the standp oint of determinacy of innite games tion lemma and certain games used in the theory of While the presentation is brief the argument is still online algorithms extremely dicult and is probably b est appreciated Intro duction y the page supplementofMonk when accompanied b Mon We prop ose the prop ositional Mucalculus as a uniform framework for understanding and simplify In this pap er we present a new enormously sim ing the imp ortant and technically challenging -
Naïve Set Theory Basic Definitions Naïve Set Theory Is the Non-Axiomatic Treatment of Set Theory
Naïve Set Theory Basic Definitions Naïve set theory is the non-axiomatic treatment of set theory. In the axiomatic treatment, which we will only allude to at times, a set is an undefined term. For us however, a set will be thought of as a collection of some (possibly none) objects. These objects are called the members (or elements) of the set. We use the symbol "∈" to indicate membership in a set. Thus, if A is a set and x is one of its members, we write x ∈ A and say "x is an element of A" or "x is in A" or "x is a member of A". Note that "∈" is not the same as the Greek letter "ε" epsilon. Basic Definitions Sets can be described notationally in many ways, but always using the set brackets "{" and "}". If possible, one can just list the elements of the set: A = {1,3, oranges, lions, an old wad of gum} or give an indication of the elements: ℕ = {1,2,3, ... } ℤ = {..., -2,-1,0,1,2, ...} or (most frequently in mathematics) using set-builder notation: S = {x ∈ ℝ | 1 < x ≤ 7 } or {x ∈ ℝ : 1 < x ≤ 7 } which is read as "S is the set of real numbers x, such that x is greater than 1 and less than or equal to 7". In some areas of mathematics sets may be denoted by special notations. For instance, in analysis S would be written (1,7]. Basic Definitions Note that sets do not contain repeated elements. An element is either in or not in a set, never "in the set 5 times" for instance. -
Regularity Properties and Determinacy
Regularity Properties and Determinacy MSc Thesis (Afstudeerscriptie) written by Yurii Khomskii (born September 5, 1980 in Moscow, Russia) under the supervision of Dr. Benedikt L¨owe, and submitted to the Board of Examiners in partial fulfillment of the requirements for the degree of MSc in Logic at the Universiteit van Amsterdam. Date of the public defense: Members of the Thesis Committee: August 14, 2007 Dr. Benedikt L¨owe Prof. Dr. Jouko V¨a¨an¨anen Prof. Dr. Joel David Hamkins Prof. Dr. Peter van Emde Boas Brian Semmes i Contents 0. Introduction............................ 1 1. Preliminaries ........................... 4 1.1 Notation. ........................... 4 1.2 The Real Numbers. ...................... 5 1.3 Trees. ............................. 6 1.4 The Forcing Notions. ..................... 7 2. ClasswiseConsequencesofDeterminacy . 11 2.1 Regularity Properties. .................... 11 2.2 Infinite Games. ........................ 14 2.3 Classwise Implications. .................... 16 3. The Marczewski-Burstin Algebra and the Baire Property . 20 3.1 MB and BP. ......................... 20 3.2 Fusion Sequences. ...................... 23 3.3 Counter-examples. ...................... 26 4. DeterminacyandtheBaireProperty.. 29 4.1 Generalized MB-algebras. .................. 29 4.2 Determinacy and BP(P). ................... 31 4.3 Determinacy and wBP(P). .................. 34 5. Determinacy andAsymmetric Properties. 39 5.1 The Asymmetric Properties. ................. 39 5.2 The General Definition of Asym(P). ............. 43 5.3 Determinacy and Asym(P). ................. 46 ii iii 0. Introduction One of the most intriguing developments of modern set theory is the investi- gation of two-player infinite games of perfect information. Of course, it is clear that applied game theory, as any other branch of mathematics, can be modeled in set theory. But we are talking about the converse: the use of infinite games as a tool to study fundamental set theoretic questions. -
Set (Mathematics) from Wikipedia, the Free Encyclopedia
Set (mathematics) From Wikipedia, the free encyclopedia A set in mathematics is a collection of well defined and distinct objects, considered as an object in its own right. Sets are one of the most fundamental concepts in mathematics. Developed at the end of the 19th century, set theory is now a ubiquitous part of mathematics, and can be used as a foundation from which nearly all of mathematics can be derived. In mathematics education, elementary topics such as Venn diagrams are taught at a young age, while more advanced concepts are taught as part of a university degree. Contents The intersection of two sets is made up of the objects contained in 1 Definition both sets, shown in a Venn 2 Describing sets diagram. 3 Membership 3.1 Subsets 3.2 Power sets 4 Cardinality 5 Special sets 6 Basic operations 6.1 Unions 6.2 Intersections 6.3 Complements 6.4 Cartesian product 7 Applications 8 Axiomatic set theory 9 Principle of inclusion and exclusion 10 See also 11 Notes 12 References 13 External links Definition A set is a well defined collection of objects. Georg Cantor, the founder of set theory, gave the following definition of a set at the beginning of his Beiträge zur Begründung der transfiniten Mengenlehre:[1] A set is a gathering together into a whole of definite, distinct objects of our perception [Anschauung] and of our thought – which are called elements of the set. The elements or members of a set can be anything: numbers, people, letters of the alphabet, other sets, and so on. -
The Axiom of Choice
THE AXIOM OF CHOICE THOMAS J. JECH State University of New York at Bufalo and The Institute for Advanced Study Princeton, New Jersey 1973 NORTH-HOLLAND PUBLISHING COMPANY - AMSTERDAM LONDON AMERICAN ELSEVIER PUBLISHING COMPANY, INC. - NEW YORK 0 NORTH-HOLLAND PUBLISHING COMPANY - 1973 AN Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior permission of the Copyright owner. Library of Congress Catalog Card Number 73-15535 North-Holland ISBN for the series 0 7204 2200 0 for this volume 0 1204 2215 2 American Elsevier ISBN 0 444 10484 4 Published by: North-Holland Publishing Company - Amsterdam North-Holland Publishing Company, Ltd. - London Sole distributors for the U.S.A. and Canada: American Elsevier Publishing Company, Inc. 52 Vanderbilt Avenue New York, N.Y. 10017 PRINTED IN THE NETHERLANDS To my parents PREFACE The book was written in the long Buffalo winter of 1971-72. It is an attempt to show the place of the Axiom of Choice in contemporary mathe- matics. Most of the material covered in the book deals with independence and relative strength of various weaker versions and consequences of the Axiom of Choice. Also included are some other results that I found relevant to the subject. The selection of the topics and results is fairly comprehensive, nevertheless it is a selection and as such reflects the personal taste of the author. So does the treatment of the subject. The main tool used throughout the text is Cohen’s method of forcing. -
The Duality of Similarity and Metric Spaces
applied sciences Article The Duality of Similarity and Metric Spaces OndˇrejRozinek 1,2,* and Jan Mareš 1,3,* 1 Department of Process Control, Faculty of Electrical Engineering and Informatics, University of Pardubice, 530 02 Pardubice, Czech Republic 2 CEO at Rozinet s.r.o., 533 52 Srch, Czech Republic 3 Department of Computing and Control Engineering, Faculty of Chemical Engineering, University of Chemistry and Technology, 166 28 Prague, Czech Republic * Correspondence: [email protected] (O.R.); [email protected] (J.M.) Abstract: We introduce a new mathematical basis for similarity space. For the first time, we describe the relationship between distance and similarity from set theory. Then, we derive generally valid relations for the conversion between similarity and a metric and vice versa. We present a general solution for the normalization of a given similarity space or metric space. The derived solutions lead to many already used similarity and distance functions, and combine them into a unified theory. The Jaccard coefficient, Tanimoto coefficient, Steinhaus distance, Ruzicka similarity, Gaussian similarity, edit distance and edit similarity satisfy this relationship, which verifies our fundamental theory. Keywords: similarity metric; similarity space; distance metric; metric space; normalized similarity metric; normalized distance metric; edit distance; edit similarity; Jaccard coefficient; Gaussian similarity 1. Introduction Mathematical spaces have been studied for centuries and belong to the basic math- ematical theories, which are used in various real-world applications [1]. In general, a mathematical space is a set of mathematical objects with an associated structure. This Citation: Rozinek, O.; Mareš, J. The structure can be specified by a number of operations on the objects of the set.