L5 Set Operations.

Slides:



Advertisements
Similar presentations
Set Operations. When sets are equal A equals B iff for all x, x is in A iff x is in B or … and this is what we do to prove sets equal.
Advertisements

Union Definition: The union of sets A and B, denoted by A B, contains those elements that are in A or B or both: Example: { 1, 2, 3} {3, 4, 5} = { 1,
Prof. Johnnie Baker Module Basic Structures: Sets
Discrete Mathematics Lecture 5 Alexander Bukharovich New York University.
Basic Structures: Sets, Functions, Sequences, Sums, and Matrices
Discrete Structures & Algorithms Basics of Set Theory EECE 320 — UBC.
Instructor: Hayk Melikya
Basic Structures: Sets, Functions, Sequences, Sums, and Matrices
Denoting the beginning
1 Section 1.7 Set Operations. 2 Union The union of 2 sets A and B is the set containing elements found either in A, or in B, or in both The denotation.
Copyright © Zeph Grunschlag, Set Operations Zeph Grunschlag.
Sets 1.
Sets 1.
1 Discussion #21 Discussion #21 Sets & Set Operations; Tuples & Relations.
1 Set Operations CS/APMA 202, Spring 2005 Rosen, section 1.7 Aaron Bloomfield.
Rosen 1.6. Approaches to Proofs Membership tables (similar to truth tables) Convert to a problem in propositional logic, prove, then convert back Use.
Set theory Sets: Powerful tool in computer science to solve real world problems. A set is a collection of distinct objects called elements. Traditionally,
Course Outline Book: Discrete Mathematics by K. P. Bogart Topics:
Chapter 3 – Set Theory  .
Boolean Algebra and Computer Logic Mathematical Structures for Computer Science Chapter 7.1 – 7.2 Copyright © 2006 W.H. Freeman & Co.MSCS Slides Boolean.
Set, Combinatorics, Probability & Number Theory Mathematical Structures for Computer Science Chapter 3 Copyright © 2006 W.H. Freeman & Co.MSCS Slides Set,
Mathematical Preliminaries (Hein 1.1 and 1.2) Sets are collections in which order of elements and duplication of elements do not matter. – {1,a,1,1} =
CS 103 Discrete Structures Lecture 10 Basic Structures: Sets (1)
Barnett/Ziegler/Byleen Finite Mathematics 11e1 Chapter 7 Review Important Terms, Symbols, Concepts 7.1. Logic A proposition is a statement (not a question.
Discrete Structure Sets. 2 Set Theory Set: Collection of objects (“elements”) a  A “a is an element of A” “a is a member of A” a  A “a is not an element.
CS201: Data Structures and Discrete Mathematics I
CompSci 102 Discrete Math for Computer Science
Fall 2008/2009 I. Arwa Linjawi & I. Asma’a Ashenkity 11 Basic Structure : Sets, Functions, Sequences, and Sums Sets Operations.
2.1 Sets 2.2 Set Operations –Set Operations –Venn Diagrams –Set Identities –Union and Intersection of Indexed Collections 2.3 Functions 2.4 Sequences and.
Chapter 2 With Question/Answer Animations. Section 2.1.
Introduction to Set theory. Ways of Describing Sets.
Discrete Mathematics CS 2610 January 27, part 2.
Discrete Mathematics Set.
Set Theory Concepts Set – A collection of “elements” (objects, members) denoted by upper case letters A, B, etc. elements are lower case brackets are used.
Module #3 - Sets 3/2/2016(c) , Michael P. Frank 2. Sets and Set Operations.
Set Operations Section 2.2.
Discrete Mathematics CS 2610 August 31, Agenda Set Theory Set Builder Notation Universal Set Power Set and Cardinality Set Operations Set Identities.
Chapter 2 1. Chapter Summary Sets (This Slide) The Language of Sets - Sec 2.1 – Lecture 8 Set Operations and Set Identities - Sec 2.2 – Lecture 9 Functions.
Introduction to Set Theory (§1.6) A set is a new type of structure, representing an unordered collection (group, plurality) of zero or more distinct (different)
CPCS 222 Discrete Structures I
Section 6.1 Set and Set Operations. Set: A set is a collection of objects/elements. Ex. A = {w, a, r, d} Sets are often named with capital letters. Order.
Set Operators Goals Show how set identities are established
Set. Outline Universal Set Venn Diagram Operations on Sets.
Dr. Ameria Eldosoky Discrete mathematics
Chapter 2 Sets and Functions.
Set Definition: A set is unordered collection of objects.
CHAPTER 3 SETS, BOOLEAN ALGEBRA & LOGIC CIRCUITS
The Language of Sets If S is a set, then
Set Operations CS 202, Spring 2008 Epp, chapter 5.
Copyright © Zeph Grunschlag,
Discrete Structures – CNS 2300
Discrete Mathematical The Set Theory
Set, Combinatorics, Probability & Number Theory
COT 3100, Spring 2001 Applications of Discrete Structures
Sets Section 2.1.
Chapter 1 Logic and Proofs Homework 2 Given the statement “A valid password is necessary for you to log on to the campus server.” Express the statement.
Taibah University College of Computer Science & Engineering Course Title: Discrete Mathematics Code: CS 103 Chapter 2 Sets Slides are adopted from “Discrete.
CS100: Discrete structures
Set Theory A B C.
Propositional Calculus: Boolean Algebra and Simplification
Set Operations Section 2.2.
Discrete Mathematics CS 2610
ICS 253: Discrete Structures I
Chapter 7 Logic, Sets, and Counting
2.1 – Symbols and Terminology
Logic Logic is a discipline that studies the principles and methods used to construct valid arguments. An argument is a related sequence of statements.
Copyright © Zeph Grunschlag,
Copyright © Zeph Grunschlag,
Set Theoretic Operations
CSC102 - Discrete Structures (Discrete Mathematics) Set Operations
Presentation transcript:

L5 Set Operations

Agenda Section 1.5: Set Operations Union  and Disjoint union Intersection  Difference “-” Complement “ ” Symmetric Difference  L5

L5 Universe of Reference When talking about a set, a universe of reference (universal set ) needs to be specified. Even though a set is defined by the elements which it contains, those elements cannot be arbitrary. If arbitrary elements are allowed paradoxes can result arising from self reference. L5

Set Builder Notation Up to now sets have been defined using the curly brace notation “{ … }” or descriptively “the set of all natural numbers”. The set builder notation allows for concise definition of new sets. For example { x | x is an even integer } { 2x | x is an integer } are equivalent ways of specifying the set of all even integers. L5

“the set of all elements f (x ) such that P (x ) holds” Set Builder Notation In general, one specifies a set by writing { f (x ) | P (x ) } Where f (x ) is a function of x and P (x ) is a propositional function of x. The notation is read as “the set of all elements f (x ) such that P (x ) holds” Stuff between “{“ and “|” specifies how elements look Stuff between the “|” and “}” gives properties elements satisfy Pipe symbol “|” is short-hand for “such that”. We can think of set builder notation analogously to a WHILE loop in a programming language. P(x) specifies the condition satisfied in the WHILE loop and f(x) is the output the from the WHILE loop. L5

Set Builder Notation. Shortcuts. To specify a subset of a pre-defined set, f (x ) takes the form xS. For example {x  N | y (x = 2y ) } defines the set of all even natural numbers (assuming universe of reference Z). When universe of reference is understood, don’t need to specify propositional function EG: { x 3 | } or simply {x 3 } specifies the set of perfect cubes {0,1,8,27,64,125, …} assuming U is the set of natural numbers. L5

Set Builder Notation. Examples. Q1: U = N. { x | y (y  x ) } = ? Q2: U = Z. { x | y (y  x ) } = ? Q3: U = Z. { x | y (y  R  y 2 = x )} = ? Q4: U = Z. { x | y (y  R  y 3 = x )} = ? Q5: U = R. { |x | | x  Z } = ? Q6: U = R. { |x | } = ? L5

Set Builder Notation. Examples. A1: U = N. { x | y (y  x ) } = { 0 } A2: U = Z. { x | y (y  x ) } = { } A3: U = Z. { x | y (y  R  y 2 = x )} = { 0, 1, 2, 3, 4, … } = N A4: U = Z. { x | y (y  R  y 3 = x )} = Z A5: U = R. { |x | | x  Z } = N A6: U = R. { |x | } = non-negative reals. L5

Set Theoretic Operations Set theoretic operations allow us to build new sets out of old, just as the logical connectives allowed us to create compound propositions from simpler propositions. Given sets A and B, the set theoretic operators are: Union () Intersection () Difference (-) Complement (“—”) Symmetric Difference () give us new sets AB, AB, A-B, AB, andA . L5

Venn Diagrams Venn diagrams are useful in representing sets and set operations. Various sets are represented by circles inside a big rectangle representing the universe of reference. L5

Elements in at least one of the two sets: Union Elements in at least one of the two sets: AB = { x | x  A  x  B } U AB A B L5

Elements in exactly one of the two sets: Intersection Elements in exactly one of the two sets: AB = { x | x  A  x  B } U A AB B L5

Disjoint Sets U A B DEF: If A and B have no common elements, they are said to be disjoint, i.e. A B =  . U A B L5

Disjoint Union When A and B are disjoint, the disjoint union operation is well defined. The circle above the union symbol indicates disjointedness. U A B L5

Disjoint Union FACT: In a disjoint union of finite sets, cardinality of the union is the sum of the cardinalities. I.e. L5

Elements in first set but not second: Set Difference Elements in first set but not second: A-B = { x | x  A  x  B } U A-B B A L5

Elements in exactly one of the two sets: Symmetric Difference Elements in exactly one of the two sets: AB = { x | x  A  x  B } AB U A B L5

Elements not in the set (unary operator): Complement Elements not in the set (unary operator): A = { x | x  A } U A A L5

Set Identities Table 1, Rosen p. 49 Identity laws Domination laws Idempotent laws Double complementation Commutativity Associativity Distribuitivity DeMorgan This table is gotten from the previous table of logical identities (Table 5, p. 17) by rewriting as follows: disjunction “” becomes union “” conjunction “” becomes intersection “” negation “” becomes complementation “–” false “F” becomes the empty set  true “T” becomes the universe of reference U L5

Set Identities In fact, the logical identities create the set identities by applying the definitions of the various set operations. For example: LEMMA: (Associativity of Unions) (AB )C = A(B C ) L5

Set Identities In fact, the logical identities create the set identities by applying the definitions of the various set operations. For example: LEMMA: (Associativity of Unions) (AB )C = A(B C ) Proof : (AB )C = {x | x  A B  x  C } (by def.) L5

Set Identities In fact, the logical identities create the set identities by applying the definitions of the various set operations. For example: LEMMA: (Associativity of Unions) (AB )C = A(B C ) Proof : (AB )C = {x | x  A B  x  C } (by def.) = {x | (x  A  x  B )  x  C } (by def.) L5

Set Identities In fact, the logical identities create the set identities by applying the definitions of the various set operations. For example: LEMMA: (Associativity of Unions) (AB )C = A(B C ) Proof : (AB )C = {x | x  A B  x  C } (by def.) = {x | (x  A  x  B )  x  C } (by def.) = {x | x  A  ( x  B  x  C ) } (logical assoc.) L5

Set Identities In fact, the logical identities create the set identities by applying the definitions of the various set operations. For example: LEMMA: (Associativity of Unions) (AB )C = A(B C ) Proof : (AB )C = {x | x  A B  x  C } (by def.) = {x | (x  A  x  B )  x  C } (by def.) = {x | x  A  ( x  B  x  C ) } (logical assoc.) = {x | x  A  x  B  C ) } (by def.) L5

Set Identities In fact, the logical identities create the set identities by applying the definitions of the various set operations. For example: LEMMA: (Associativity of Unions) (AB )C = A(B C ) Proof : (AB )C = {x | x  A B  x  C } (by def.) = {x | (x  A  x  B )  x  C } (by def.) = {x | x  A  ( x  B  x  C ) } (logical assoc.) = {x | x  A  (x  B  C ) } (by def.) = A(B C ) (by def.)  Other identities are derived similarly. L5

Set Identities via Venn It’s often simpler to understand an identity by drawing a Venn Diagram. For example DeMorgan’s first law can be visualized as follows. L5

Visual DeMorgan B: A: L5

Visual DeMorgan B: A: AB : L5

Visual DeMorgan B: A: AB : L5

Visual DeMorgan B: A: L5

Visual DeMorgan B: A: A: B: L5

Visual DeMorgan B: A: A: B: L5

Visual DeMorgan = L5

U = {ant, beetle, cicada, dragonfly} Sets as Bit-Strings If we order the elements of our universe, we can represent sets by bit-strings. For example, consider the universe U = {ant, beetle, cicada, dragonfly} Order the elements alphabetically. Subsets of U are represented by bit-strings of length 4. Each bit in turn, tells us whether the corresponding element is contained in the set. EG: {ant, dragonfly} is represented by the bit-string 1001. Q: What set is represented by 0111 ? L5

Sets as Bit-Strings  1101 A: 0111 represents {beetle, cicada, dragonfly} Conveniently, under this representation the various set theoretic operations become the logical bit-string operators that we saw before. For example, the symmetric difference of {beetle} with {ant, beetle, dragonfly} is represented by: 0100  1101 1001 = {ant, dragonfly} L5