Measures in Boolean Algebras
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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). -
Dynamic Algebras: Examples, Constructions, Applications
Dynamic Algebras: Examples, Constructions, Applications Vaughan Pratt∗ Dept. of Computer Science, Stanford, CA 94305 Abstract Dynamic algebras combine the classes of Boolean (B ∨ 0 0) and regu- lar (R ∪ ; ∗) algebras into a single finitely axiomatized variety (BR 3) resembling an R-module with “scalar” multiplication 3. The basic result is that ∗ is reflexive transitive closure, contrary to the intuition that this concept should require quantifiers for its definition. Using this result we give several examples of dynamic algebras arising naturally in connection with additive functions, binary relations, state trajectories, languages, and flowcharts. The main result is that free dynamic algebras are residu- ally finite (i.e. factor as a subdirect product of finite dynamic algebras), important because finite separable dynamic algebras are isomorphic to Kripke structures. Applications include a new completeness proof for the Segerberg axiomatization of propositional dynamic logic, and yet another notion of regular algebra. Key words: Dynamic algebra, logic, program verification, regular algebra. This paper originally appeared as Technical Memo #138, Laboratory for Computer Science, MIT, July 1979, and was subsequently revised, shortened, retitled, and published as [Pra80b]. After more than a decade of armtwisting I. N´emeti and H. Andr´eka finally persuaded the author to publish TM#138 itself on the ground that it contained a substantial body of interesting material that for the sake of brevity had been deleted from the STOC-80 version. The principal changes here to TM#138 are the addition of footnotes and the sections at the end on retrospective citations and reflections. ∗This research was supported by the National Science Foundation under NSF grant no. -
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. -
A Combinatorial Analysis of Finite Boolean Algebras
A Combinatorial Analysis of Finite Boolean Algebras Kevin Halasz [email protected] May 1, 2013 Copyright c Kevin Halasz. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license can be found at http://www.gnu.org/copyleft/fdl.html. 1 Contents 1 Introduction 3 2 Basic Concepts 3 2.1 Chains . .3 2.2 Antichains . .6 3 Dilworth's Chain Decomposition Theorem 6 4 Boolean Algebras 8 5 Sperner's Theorem 9 5.1 The Sperner Property . .9 5.2 Sperner's Theorem . 10 6 Extensions 12 6.1 Maximally Sized Antichains . 12 6.2 The Erdos-Ko-Rado Theorem . 13 7 Conclusion 14 2 1 Introduction Boolean algebras serve an important purpose in the study of algebraic systems, providing algebraic structure to the notions of order, inequality, and inclusion. The algebraist is always trying to understand some structured set using symbol manipulation. Boolean algebras are then used to study the relationships that hold between such algebraic structures while still using basic techniques of symbol manipulation. In this paper we will take a step back from the standard algebraic practices, and analyze these fascinating algebraic structures from a different point of view. Using combinatorial tools, we will provide an in-depth analysis of the structure of finite Boolean algebras. We will start by introducing several ways of analyzing poset substructure from a com- binatorial point of view. -
A Boolean Algebra and K-Map Approach
Proceedings of the International Conference on Industrial Engineering and Operations Management Washington DC, USA, September 27-29, 2018 Reliability Assessment of Bufferless Production System: A Boolean Algebra and K-Map Approach Firas Sallumi ([email protected]) and Walid Abdul-Kader ([email protected]) Industrial and Manufacturing Systems Engineering University of Windsor, Windsor (ON) Canada Abstract In this paper, system reliability is determined based on a K-map (Karnaugh map) and the Boolean algebra theory. The proposed methodology incorporates the K-map technique for system level reliability, and Boolean analysis for interactions. It considers not only the configuration of the production line, but also effectively incorporates the interactions between the machines composing the line. Through the K-map, a binary argument is used for considering the interactions between the machines and a probability expression is found to assess the reliability of a bufferless production system. The paper covers three main system design configurations: series, parallel and hybrid (mix of series and parallel). In the parallel production system section, three strategies or methods are presented to find the system reliability. These are the Split, the Overlap, and the Zeros methods. A real-world case study from the automotive industry is presented to demonstrate the applicability of the approach used in this research work. Keywords: Series, Series-Parallel, Hybrid, Bufferless, Production Line, Reliability, K-Map, Boolean algebra 1. Introduction Presently, the global economy is forcing companies to have their production systems maintain low inventory and provide short delivery times. Therefore, production systems are required to be reliable and productive to make products at rates which are changing with the demand. -
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 . -
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. -
Sets and Boolean Algebra
MATHEMATICAL THEORY FOR SOCIAL SCIENTISTS SETS AND SUBSETS Denitions (1) A set A in any collection of objects which have a common characteristic. If an object x has the characteristic, then we say that it is an element or a member of the set and we write x ∈ A.Ifxis not a member of the set A, then we write x/∈A. It may be possible to specify a set by writing down all of its elements. If x, y, z are the only elements of the set A, then the set can be written as (2) A = {x, y, z}. Similarly, if A is a nite set comprising n elements, then it can be denoted by (3) A = {x1,x2,...,xn}. The three dots, which stand for the phase “and so on”, are called an ellipsis. The subscripts which are applied to the x’s place them in a one-to-one cor- respondence with set of integers {1, 2,...,n} which constitutes the so-called index set. However, this indexing imposes no necessary order on the elements of the set; and its only pupose is to make it easier to reference the elements. Sometimes we write an expression in the form of (4) A = {x1,x2,...}. Here the implication is that the set A may have an innite number of elements; in which case a correspondence is indicated between the elements of the set and the set of natural numbers or positive integers which we shall denote by (5) Z = {1, 2,...}. (Here the letter Z, which denotes the set of natural numbers, derives from the German verb zahlen: to count) An alternative way of denoting a set is to specify the characteristic which is common to its elements. -
Boolean Algebras
CHAPTER 8 Boolean Algebras 8.1. Combinatorial Circuits 8.1.1. Introduction. At their lowest level digital computers han- dle only binary signals, represented with the symbols 0 and 1. The most elementary circuits that combine those signals are called gates. Figure 8.1 shows three gates: OR, AND and NOT. x1 OR GATE x1 x2 x2 x1 AND GATE x1 x2 x2 NOT GATE x x Figure 8.1. Gates. Their outputs can be expressed as a function of their inputs by the following logic tables: x1 x2 x1 x2 1 1 ∨1 1 0 1 0 1 1 0 0 0 OR GATE 118 8.1. COMBINATORIAL CIRCUITS 119 x1 x2 x1 x2 1 1 ∧1 1 0 0 0 1 0 0 0 0 AND GATE x x¯ 1 0 0 1 NOT GATE These are examples of combinatorial circuits. A combinatorial cir- cuit is a circuit whose output is uniquely defined by its inputs. They do not have memory, previous inputs do not affect their outputs. Some combinations of gates can be used to make more complicated combi- natorial circuits. For instance figure 8.2 is combinatorial circuit with the logic table shown below, representing the values of the Boolean expression y = (x x ) x . 1 ∨ 2 ∧ 3 x1 x2 y x3 Figure 8.2. A combinatorial circuit. x1 x2 x3 y = (x1 x2) x3 1 1 1 ∨0 ∧ 1 1 0 1 1 0 1 0 1 0 0 1 0 1 1 0 0 1 0 1 0 0 1 1 0 0 0 1 However the circuit in figure 8.3 is not a combinatorial circuit. -
Boolean Algebra.Pdf
Section 3 Boolean Algebra The Building Blocks of Digital Logic Design Section Overview Binary Operations (AND, OR, NOT), Basic laws, Proof by Perfect Induction, De Morgan’s Theorem, Canonical and Standard Forms (SOP, POS), Gates as SSI Building Blocks (Buffer, NAND, NOR, XOR) Source: UCI Lecture Series on Computer Design — Gates as Building Blocks, Digital Design Sections 1-9 and 2-1 to 2-7, Digital Logic Design CECS 201 Lecture Notes by Professor Allison Section II — Boolean Algebra and Logic Gates, Digital Computer Fundamentals Chapter 4 — Boolean Algebra and Gate Networks, Principles of Digital Computer Design Chapter 5 — Switching Algebra and Logic Gates, Computer Hardware Theory Section 6.3 — Remarks about Boolean Algebra, An Introduction To Microcomputers pp. 2-7 to 2-10 — Boolean Algebra and Computer Logic. Sessions: Four(4) Topics: 1) Binary Operations and Their Representation 2) Basic Laws and Theorems of Boolean Algebra 3) Derivation of Boolean Expressions (Sum-of-products and Product-of-sums) 4) Reducing Algebraic Expressions 5) Converting an Algebraic Expression into Logic Gates 6) From Logic Gates to SSI Circuits Binary Operations and Their Representation The Problem Modern digital computers are designed using techniques and symbology from a field of mathematics called modern algebra. Algebraists have studied for a period of over a hundred years mathematical systems called Boolean algebras. Nothing could be more simple and normal to human reasoning than the rules of a Boolean algebra, for these originated in studies of how we reason, what lines of reasoning are valid, what constitutes proof, and other allied subjects. The name Boolean algebra honors a fascinating English mathematician, George Boole, who in 1854 published a classic book, "An Investigation of the Laws of Thought, on Which Are Founded the Mathematical Theories of Logic and Probabilities." Boole's stated intention was to perform a mathematical analysis of logic. -
Boolean Algebra
Boolean Algebra ECE 152A – Winter 2012 Reading Assignment Brown and Vranesic 2 Introduction to Logic Circuits 2.5 Boolean Algebra 2.5.1 The Venn Diagram 2.5.2 Notation and Terminology 2.5.3 Precedence of Operations 2.6 Synthesis Using AND, OR and NOT Gates 2.6.1 Sum-of-Products and Product of Sums Forms January 11, 2012 ECE 152A - Digital Design Principles 2 Reading Assignment Brown and Vranesic (cont) 2 Introduction to Logic Circuits (cont) 2.7 NAND and NOR Logic Networks 2.8 Design Examples 2.8.1 Three-Way Light Control 2.8.2 Multiplexer Circuit January 11, 2012 ECE 152A - Digital Design Principles 3 Reading Assignment Roth 2 Boolean Algebra 2.3 Boolean Expressions and Truth Tables 2.4 Basic Theorems 2.5 Commutative, Associative, and Distributive Laws 2.6 Simplification Theorems 2.7 Multiplying Out and Factoring 2.8 DeMorgan’s Laws January 11, 2012 ECE 152A - Digital Design Principles 4 Reading Assignment Roth (cont) 3 Boolean Algebra (Continued) 3.1 Multiplying Out and Factoring Expressions 3.2 Exclusive-OR and Equivalence Operation 3.3 The Consensus Theorem 3.4 Algebraic Simplification of Switching Expressions January 11, 2012 ECE 152A - Digital Design Principles 5 Reading Assignment Roth (cont) 4 Applications of Boolean Algebra Minterm and Maxterm Expressions 4.3 Minterm and Maxterm Expansions 7 Multi-Level Gate Circuits NAND and NOR Gates 7.2 NAND and NOR Gates 7.3 Design of Two-Level Circuits Using NAND and NOR Gates 7.5 Circuit Conversion Using Alternative Gate Symbols January 11, 2012 ECE 152A - Digital Design Principles 6 Boolean Algebra Axioms of Boolean Algebra Axioms generally presented without proof 0 · 0 = 0 1 + 1 = 1 1 · 1 = 1 0 + 0 = 0 0 · 1 = 1 · 0 = 0 1 + 0 = 0 + 1 = 1 if X = 0, then X’ = 1 if X = 1, then X’ = 0 January 11, 2012 ECE 152A - Digital Design Principles 7 Boolean Algebra The Principle of Duality from Zvi Kohavi, Switching and Finite Automata Theory “We observe that all the preceding properties are grouped in pairs. -
Boolean Algebra Computer Fundamentals
CCoommppuutterer FFununddaammenenttaallss:: PPrradadeeepep KK.. SSiinhanha && PPrriititi SSiinhanha Ref. Page Chapter 6: Boolean Algebra and Logic Circuits Slide 1/78 CCoommppuutterer FFununddaammenenttaallss:: PPrradadeeepep KK.. SSiinhanha && PPrriititi SSiinhanha LLeeararnniinngg ObObjjeeccttiivveses In this chapter you will learn about: § Boolean algebra § Fundamental concepts and basic laws of Boolean algebra § Boolean function and minimization § Logic gates § Logic circuits and Boolean expressions § Combinational circuits and design Ref. Page 60 Chapter 6: Boolean Algebra and Logic Circuits Slide 2/78 CCoommppuutterer FFununddaammenenttaallss:: PPrradadeeepep KK.. SSiinhanha && PPrriititi SSiinhanha BBooooleleaann AAllggeebrabra § An algebra that deals with binary number system § George Boole (1815-1864), an English mathematician, developed it for: § Simplifying representation § Manipulation of propositional logic § In 1938, Claude E. Shannon proposed using Boolean algebra in design of relay switching circuits § Provides economical and straightforward approach § Used extensively in designing electronic circuits used in computers Ref. Page 60 Chapter 6: Boolean Algebra and Logic Circuits Slide 3/78 CCoommppuutterer FFununddaammenenttaallss:: PPrradadeeepep KK.. SSiinhanha && PPrriititi SSiinhanha FundamFundameennttalal CCoonncceeppttss ooffBBoooolleeaann AAlglgeebbrara § Use of Binary Digit § Boolean equations can have either of two possible values, 0 and 1 § Logical Addition § Symbol ‘+’, also known as ‘OR’operator, used for logical