SlideShare a Scribd company logo
Ajeela Mushtaq Roll NO:-13-Mcs-15
PRESENTED TO:-PRESENTED TO:-
MR. MIR AADIL
SETSSETS
Introduction
•Definition: A set is an unordered collection
of (unique) objects.
•Sets are fundamental discrete structures
and for the basis of more complex discrete
structures like graphs
• Definition: The objects in a set are
called elements or members of a set.
A set is said to contain its elements.
• Notation, for a set A:
– x  A: x is an element of A
– x  A: x is not an element of A
Terminology
• Definition: Two sets, A and B, are equal
is they contain the same elements. We
write A=B.
• Example:
– {2,3,5,7}={3,2,7,5}, because a set is
unordered
– Also, {2,3,5,7}={2,2,3,5,3,7} because a set
contains unique elements
– However, {2,3,5,7} {2,3}
• The set-builder notation
O={ x | (xZ)  (x=2k) for some kZ}
reads: O is the set that contains all x such
that x is an integer and x is even
• A set is defined in intension when you give
its set-builder notation
O={ x | (xZ)  (0x8)  (x=2k) for some k  Z }
• A set is defined in extension when you
enumerate all the elements:
O={0,2,4,6,8}
Venn Diagram: Example
• A set can be represented graphically
using a Venn Diagram
U
a
x y
z
A
C
B
• A set that has no elements is called the empty
set or null set and is denoted 
• A set that has one element is called a
singleton set.
– For example: {a}, with brackets, is a singleton set
– a, without brackets, is an element of the set {a}
• Note the subtlety in   {}
– The left-hand side is the empty set
– The right hand-side is a singleton set, and a set
containing a set
• Definition: A is said to be a subset
of B, and we write A  B, if and only
if every element of A is also an
element of B.
• That is, we have the equivalence:
A  B   x (x  A  x  B)
• Definition: A set A that is a subset
of a set B is called a proper subset
if A  B.
• That is there is an element xB such
that xA.
• We write: A  B, A  B
• Sets can be elements of other sets.
• Examples
– S1 = {,{a},{b},{a,b},c}
– S2={{1},{2,4,8},{3},{6},4,5,6}.
• Definition: If there are exactly n
distinct elements in a set S, with n a
nonnegative integer, we say that:
– S is a finite set, and
– The cardinality of S is n. Notation: |S| =
n.
• Definition: A set that is not finite is
said to be infinite
• Examples
– Let B = {x | (x100)  (x is prime)}, the
cardinality of B is |B|=25 because there
are 25 primes less than or equal to 100.
– The cardinality of the empty set is ||=0
– The sets N, Z, Q, R are all infinite
Equivalence
• You may be asked to show that a set is
– a subset of,
– proper subset of, or
– equal to another set.
• To prove that A is a subset of B, use the equivalence
discussed earlier A  B  x(xA  xB)
– To prove that A  B it is enough to show that for an arbitrary
(nonspecific) element x, xA implies that x is also in B.
– Any proof method can be used.
• To prove that A is a proper subset of B, you must prove
– A is a subset of B and
– x (xB)  (xA)
• Finally to show that two sets are equal, it is
sufficient to show independently (much like
a biconditional) that
– A  B and
– B  A
• Logically speaking, you must show the
following quantified statements:
(x (xA  xB))  (x (xB  xA))
we will see an example later..
Power Set
• Definition: The power set of a set S,
denoted P(S), is the set of all subsets of
S.
• Examples
– Let A={a,b,c}, P(A)={,{a},{b},{c},{a,b},{b,c},
{a,c},{a,b,c}}
Let A={{a,b},c}, P(A)={,{{a,b}},{c},
{{a,b},c}}
• Fact: Let S be a set such that |S|=n, then
|P(S)| = 2n
Set Operations
• Arithmetic operators (+,-,  ,) can be
used on pairs of numbers to give us new
numbers
• Similarly, set operators exist and act on
two sets to give us new sets
– Union
– Intersection
– Set difference
– Set complement
Set Operators: Union
• Definition: The union of two sets A
and B is the set that contains all
elements in A, B, r both. We write:
AB = { x | (a  A)  (b  B) }
U
A B
Set Operators: Intersection
• Definition: The intersection of two
sets A and B is the set that contains
all elements that are element of both
A and B. We write:
A  B = { x | (a  A)  (b  B) }
U
A B
Disjoint Sets
• Definition: Two sets are said to be
disjoint if their intersection is the
empty set: A  B = 
U
A B
Set Difference
• Definition: The difference of two
sets A and B, denoted AB ($setminus$)
or A−B, is the set containing those
elements that are in A but not in B
U
A B
Set Complement
• Definition: The complement of a set
A, denoted A ($bar$), consists of all
elements not in A. That is the
difference of the universal set and U:
UA
A= AC = {x | x  A }
U A
A
Set Complement: Absolute &
Relative
• Given the Universe U, and A,B  U.
• The (absolute) complement of A is
A=UA
• The (relative) complement of A in B
is BAU
AA
U
BA

More Related Content

What's hot

Divide and conquer 1
Divide and conquer 1Divide and conquer 1
Divide and conquer 1
Kumar
 
Data Structure and Algorithms Binary Search Tree
Data Structure and Algorithms Binary Search TreeData Structure and Algorithms Binary Search Tree
Data Structure and Algorithms Binary Search Tree
ManishPrajapati78
 
Database Normalization 1NF, 2NF, 3NF, BCNF, 4NF, 5NF
Database Normalization 1NF, 2NF, 3NF, BCNF, 4NF, 5NFDatabase Normalization 1NF, 2NF, 3NF, BCNF, 4NF, 5NF
Database Normalization 1NF, 2NF, 3NF, BCNF, 4NF, 5NF
Oum Saokosal
 
Erd practice exercises
Erd practice exercisesErd practice exercises
Erd practice exercises
Jennifer Polack
 
Spanning trees
Spanning treesSpanning trees
Spanning trees
Shareb Ismaeel
 
AI_Session 10 Local search in continious space.pptx
AI_Session 10 Local search in continious space.pptxAI_Session 10 Local search in continious space.pptx
AI_Session 10 Local search in continious space.pptx
Asst.prof M.Gokilavani
 
Knowledge Representation, Inference and Reasoning
Knowledge Representation, Inference and ReasoningKnowledge Representation, Inference and Reasoning
Knowledge Representation, Inference and Reasoning
Sagacious IT Solution
 
0 1 knapsack using branch and bound
0 1 knapsack using branch and bound0 1 knapsack using branch and bound
0 1 knapsack using branch and bound
Abhishek Singh
 
Data Structure and Algorithms
Data Structure and AlgorithmsData Structure and Algorithms
Data Structure and Algorithms
iqbalphy1
 
01 knapsack using backtracking
01 knapsack using backtracking01 knapsack using backtracking
01 knapsack using backtracking
mandlapure
 
Functions in discrete mathematics
Functions in discrete mathematicsFunctions in discrete mathematics
Functions in discrete mathematics
Rachana Pathak
 
First order logic
First order logicFirst order logic
First order logic
Megha Sharma
 
The Relational Model
The Relational ModelThe Relational Model
The Relational Model
Bhandari Nawaraj
 
knapsackusingbranchandbound
knapsackusingbranchandboundknapsackusingbranchandbound
knapsackusingbranchandbound
hodcsencet
 
VISUAL BASIC 6 - CONTROLS AND DECLARATIONS
VISUAL BASIC 6 - CONTROLS AND DECLARATIONSVISUAL BASIC 6 - CONTROLS AND DECLARATIONS
VISUAL BASIC 6 - CONTROLS AND DECLARATIONS
Suraj Kumar
 
A study on connectivity in graph theory june 18 123e
A study on connectivity in graph theory  june 18 123eA study on connectivity in graph theory  june 18 123e
A study on connectivity in graph theory june 18 123e
aswathymaths
 
Crisp sets
Crisp setsCrisp sets
Crisp sets
DEEPIKA T
 
AI_Session 7 Greedy Best first search algorithm.pptx
AI_Session 7 Greedy Best first search algorithm.pptxAI_Session 7 Greedy Best first search algorithm.pptx
AI_Session 7 Greedy Best first search algorithm.pptx
Asst.prof M.Gokilavani
 
Statistical learning
Statistical learningStatistical learning
Statistical learning
Slideshare
 
CMSC 56 | Lecture 12: Recursive Definition & Algorithms, and Program Correctness
CMSC 56 | Lecture 12: Recursive Definition & Algorithms, and Program CorrectnessCMSC 56 | Lecture 12: Recursive Definition & Algorithms, and Program Correctness
CMSC 56 | Lecture 12: Recursive Definition & Algorithms, and Program Correctness
allyn joy calcaben
 

What's hot (20)

Divide and conquer 1
Divide and conquer 1Divide and conquer 1
Divide and conquer 1
 
Data Structure and Algorithms Binary Search Tree
Data Structure and Algorithms Binary Search TreeData Structure and Algorithms Binary Search Tree
Data Structure and Algorithms Binary Search Tree
 
Database Normalization 1NF, 2NF, 3NF, BCNF, 4NF, 5NF
Database Normalization 1NF, 2NF, 3NF, BCNF, 4NF, 5NFDatabase Normalization 1NF, 2NF, 3NF, BCNF, 4NF, 5NF
Database Normalization 1NF, 2NF, 3NF, BCNF, 4NF, 5NF
 
Erd practice exercises
Erd practice exercisesErd practice exercises
Erd practice exercises
 
Spanning trees
Spanning treesSpanning trees
Spanning trees
 
AI_Session 10 Local search in continious space.pptx
AI_Session 10 Local search in continious space.pptxAI_Session 10 Local search in continious space.pptx
AI_Session 10 Local search in continious space.pptx
 
Knowledge Representation, Inference and Reasoning
Knowledge Representation, Inference and ReasoningKnowledge Representation, Inference and Reasoning
Knowledge Representation, Inference and Reasoning
 
0 1 knapsack using branch and bound
0 1 knapsack using branch and bound0 1 knapsack using branch and bound
0 1 knapsack using branch and bound
 
Data Structure and Algorithms
Data Structure and AlgorithmsData Structure and Algorithms
Data Structure and Algorithms
 
01 knapsack using backtracking
01 knapsack using backtracking01 knapsack using backtracking
01 knapsack using backtracking
 
Functions in discrete mathematics
Functions in discrete mathematicsFunctions in discrete mathematics
Functions in discrete mathematics
 
First order logic
First order logicFirst order logic
First order logic
 
The Relational Model
The Relational ModelThe Relational Model
The Relational Model
 
knapsackusingbranchandbound
knapsackusingbranchandboundknapsackusingbranchandbound
knapsackusingbranchandbound
 
VISUAL BASIC 6 - CONTROLS AND DECLARATIONS
VISUAL BASIC 6 - CONTROLS AND DECLARATIONSVISUAL BASIC 6 - CONTROLS AND DECLARATIONS
VISUAL BASIC 6 - CONTROLS AND DECLARATIONS
 
A study on connectivity in graph theory june 18 123e
A study on connectivity in graph theory  june 18 123eA study on connectivity in graph theory  june 18 123e
A study on connectivity in graph theory june 18 123e
 
Crisp sets
Crisp setsCrisp sets
Crisp sets
 
AI_Session 7 Greedy Best first search algorithm.pptx
AI_Session 7 Greedy Best first search algorithm.pptxAI_Session 7 Greedy Best first search algorithm.pptx
AI_Session 7 Greedy Best first search algorithm.pptx
 
Statistical learning
Statistical learningStatistical learning
Statistical learning
 
CMSC 56 | Lecture 12: Recursive Definition & Algorithms, and Program Correctness
CMSC 56 | Lecture 12: Recursive Definition & Algorithms, and Program CorrectnessCMSC 56 | Lecture 12: Recursive Definition & Algorithms, and Program Correctness
CMSC 56 | Lecture 12: Recursive Definition & Algorithms, and Program Correctness
 

Similar to Sets automata

Set theory
Set theorySet theory
Set theory
Robert Geofroy
 
Set theory
Set theorySet theory
Set theory
Gaditek
 
Blackbox task 2
Blackbox task 2Blackbox task 2
Blackbox task 2
blackbox90s
 
Set Theory
Set Theory Set Theory
Set Theory
NISHITAKALYANI
 
SetTheory.ppt
SetTheory.pptSetTheory.ppt
SetTheory.ppt
bryanchristianbrione1
 
SetTheory.ppt
SetTheory.pptSetTheory.ppt
SetTheory.ppt
sanjeevnandwani
 
Introduction to set theory with application
Introduction to set theory with applicationIntroduction to set theory with application
Introduction to set theory with application
Okunlola Oluyemi Adewole
 
1. set theory
1. set theory1. set theory
1. set theory
caymulb
 
A set is a structure, representing an unordered collection (group, plurality)...
A set is a structure, representing an unordered collection (group, plurality)...A set is a structure, representing an unordered collection (group, plurality)...
A set is a structure, representing an unordered collection (group, plurality)...
OluyemiOkunlola
 
Mkk1013 chapter 2.1
Mkk1013 chapter 2.1Mkk1013 chapter 2.1
Mkk1013 chapter 2.1
ramlahmailok
 
sets by navneet
sets by navneetsets by navneet
sets by navneet
121kumararjun
 
INTRODUCTION TO SETS.pptx
INTRODUCTION TO SETS.pptxINTRODUCTION TO SETS.pptx
INTRODUCTION TO SETS.pptx
Sumit366794
 
Set
SetSet
Set
H K
 
Introduction to Sets
Introduction to SetsIntroduction to Sets
Introduction to Sets
Ashita Agrawal
 
Moazzzim Sir (25.07.23)CSE 1201, Week#3, Lecture#7.pptx
Moazzzim Sir (25.07.23)CSE 1201, Week#3, Lecture#7.pptxMoazzzim Sir (25.07.23)CSE 1201, Week#3, Lecture#7.pptx
Moazzzim Sir (25.07.23)CSE 1201, Week#3, Lecture#7.pptx
KhalidSyfullah6
 
sets.pptx
sets.pptxsets.pptx
Sets (Mathematics class XI)
Sets (Mathematics class XI)Sets (Mathematics class XI)
Sets (Mathematics class XI)
VihaanBhambhani
 
set.pdf
set.pdfset.pdf
set.pdf
SherazSyed3
 
sets class 11.pptx
sets class 11.pptxsets class 11.pptx
sets class 11.pptx
SaritaKadianAntil
 
Introduction to sets
Introduction to setsIntroduction to sets
Introduction to sets
Sonia Pahuja
 

Similar to Sets automata (20)

Set theory
Set theorySet theory
Set theory
 
Set theory
Set theorySet theory
Set theory
 
Blackbox task 2
Blackbox task 2Blackbox task 2
Blackbox task 2
 
Set Theory
Set Theory Set Theory
Set Theory
 
SetTheory.ppt
SetTheory.pptSetTheory.ppt
SetTheory.ppt
 
SetTheory.ppt
SetTheory.pptSetTheory.ppt
SetTheory.ppt
 
Introduction to set theory with application
Introduction to set theory with applicationIntroduction to set theory with application
Introduction to set theory with application
 
1. set theory
1. set theory1. set theory
1. set theory
 
A set is a structure, representing an unordered collection (group, plurality)...
A set is a structure, representing an unordered collection (group, plurality)...A set is a structure, representing an unordered collection (group, plurality)...
A set is a structure, representing an unordered collection (group, plurality)...
 
Mkk1013 chapter 2.1
Mkk1013 chapter 2.1Mkk1013 chapter 2.1
Mkk1013 chapter 2.1
 
sets by navneet
sets by navneetsets by navneet
sets by navneet
 
INTRODUCTION TO SETS.pptx
INTRODUCTION TO SETS.pptxINTRODUCTION TO SETS.pptx
INTRODUCTION TO SETS.pptx
 
Set
SetSet
Set
 
Introduction to Sets
Introduction to SetsIntroduction to Sets
Introduction to Sets
 
Moazzzim Sir (25.07.23)CSE 1201, Week#3, Lecture#7.pptx
Moazzzim Sir (25.07.23)CSE 1201, Week#3, Lecture#7.pptxMoazzzim Sir (25.07.23)CSE 1201, Week#3, Lecture#7.pptx
Moazzzim Sir (25.07.23)CSE 1201, Week#3, Lecture#7.pptx
 
sets.pptx
sets.pptxsets.pptx
sets.pptx
 
Sets (Mathematics class XI)
Sets (Mathematics class XI)Sets (Mathematics class XI)
Sets (Mathematics class XI)
 
set.pdf
set.pdfset.pdf
set.pdf
 
sets class 11.pptx
sets class 11.pptxsets class 11.pptx
sets class 11.pptx
 
Introduction to sets
Introduction to setsIntroduction to sets
Introduction to sets
 

More from ajeela mushtaq

String.ppt
String.pptString.ppt
String.ppt
ajeela mushtaq
 
Polymorphism
PolymorphismPolymorphism
Polymorphism
ajeela mushtaq
 
Mail merge
Mail mergeMail merge
Mail merge
ajeela mushtaq
 
Linux hotspot
Linux hotspotLinux hotspot
Linux hotspot
ajeela mushtaq
 
Interfaces .net
Interfaces .netInterfaces .net
Interfaces .net
ajeela mushtaq
 
Incremental
IncrementalIncremental
Incremental
ajeela mushtaq
 
Gprs
GprsGprs
Graphics a buffer
Graphics a bufferGraphics a buffer
Graphics a buffer
ajeela mushtaq
 
Disk allocation methods
Disk allocation methodsDisk allocation methods
Disk allocation methods
ajeela mushtaq
 
Data com prsntation
Data com prsntationData com prsntation
Data com prsntation
ajeela mushtaq
 
Avl tree
Avl treeAvl tree
Avl tree
ajeela mushtaq
 
Dynamic routing
Dynamic routingDynamic routing
Dynamic routing
ajeela mushtaq
 

More from ajeela mushtaq (12)

String.ppt
String.pptString.ppt
String.ppt
 
Polymorphism
PolymorphismPolymorphism
Polymorphism
 
Mail merge
Mail mergeMail merge
Mail merge
 
Linux hotspot
Linux hotspotLinux hotspot
Linux hotspot
 
Interfaces .net
Interfaces .netInterfaces .net
Interfaces .net
 
Incremental
IncrementalIncremental
Incremental
 
Gprs
GprsGprs
Gprs
 
Graphics a buffer
Graphics a bufferGraphics a buffer
Graphics a buffer
 
Disk allocation methods
Disk allocation methodsDisk allocation methods
Disk allocation methods
 
Data com prsntation
Data com prsntationData com prsntation
Data com prsntation
 
Avl tree
Avl treeAvl tree
Avl tree
 
Dynamic routing
Dynamic routingDynamic routing
Dynamic routing
 

Recently uploaded

06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
Timothy Spann
 
DSSML24_tspann_CodelessGenerativeAIPipelines
DSSML24_tspann_CodelessGenerativeAIPipelinesDSSML24_tspann_CodelessGenerativeAIPipelines
DSSML24_tspann_CodelessGenerativeAIPipelines
Timothy Spann
 
Analysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performanceAnalysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performance
roli9797
 
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdfUdemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Fernanda Palhano
 
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
Timothy Spann
 
一比一原版(Chester毕业证书)切斯特大学毕业证如何办理
一比一原版(Chester毕业证书)切斯特大学毕业证如何办理一比一原版(Chester毕业证书)切斯特大学毕业证如何办理
一比一原版(Chester毕业证书)切斯特大学毕业证如何办理
74nqk8xf
 
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
sameer shah
 
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Aggregage
 
一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理
aqzctr7x
 
A presentation that explain the Power BI Licensing
A presentation that explain the Power BI LicensingA presentation that explain the Power BI Licensing
A presentation that explain the Power BI Licensing
AlessioFois2
 
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
nuttdpt
 
Influence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business PlanInfluence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business Plan
jerlynmaetalle
 
一比一原版(Glasgow毕业证书)格拉斯哥大学毕业证如何办理
一比一原版(Glasgow毕业证书)格拉斯哥大学毕业证如何办理一比一原版(Glasgow毕业证书)格拉斯哥大学毕业证如何办理
一比一原版(Glasgow毕业证书)格拉斯哥大学毕业证如何办理
g4dpvqap0
 
Global Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headedGlobal Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headed
vikram sood
 
End-to-end pipeline agility - Berlin Buzzwords 2024
End-to-end pipeline agility - Berlin Buzzwords 2024End-to-end pipeline agility - Berlin Buzzwords 2024
End-to-end pipeline agility - Berlin Buzzwords 2024
Lars Albertsson
 
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
Social Samosa
 
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
nuttdpt
 
The Ipsos - AI - Monitor 2024 Report.pdf
The  Ipsos - AI - Monitor 2024 Report.pdfThe  Ipsos - AI - Monitor 2024 Report.pdf
The Ipsos - AI - Monitor 2024 Report.pdf
Social Samosa
 
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataPredictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Kiwi Creative
 
Experts live - Improving user adoption with AI
Experts live - Improving user adoption with AIExperts live - Improving user adoption with AI
Experts live - Improving user adoption with AI
jitskeb
 

Recently uploaded (20)

06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
 
DSSML24_tspann_CodelessGenerativeAIPipelines
DSSML24_tspann_CodelessGenerativeAIPipelinesDSSML24_tspann_CodelessGenerativeAIPipelines
DSSML24_tspann_CodelessGenerativeAIPipelines
 
Analysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performanceAnalysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performance
 
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdfUdemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
 
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
 
一比一原版(Chester毕业证书)切斯特大学毕业证如何办理
一比一原版(Chester毕业证书)切斯特大学毕业证如何办理一比一原版(Chester毕业证书)切斯特大学毕业证如何办理
一比一原版(Chester毕业证书)切斯特大学毕业证如何办理
 
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
 
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
 
一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理
 
A presentation that explain the Power BI Licensing
A presentation that explain the Power BI LicensingA presentation that explain the Power BI Licensing
A presentation that explain the Power BI Licensing
 
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
 
Influence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business PlanInfluence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business Plan
 
一比一原版(Glasgow毕业证书)格拉斯哥大学毕业证如何办理
一比一原版(Glasgow毕业证书)格拉斯哥大学毕业证如何办理一比一原版(Glasgow毕业证书)格拉斯哥大学毕业证如何办理
一比一原版(Glasgow毕业证书)格拉斯哥大学毕业证如何办理
 
Global Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headedGlobal Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headed
 
End-to-end pipeline agility - Berlin Buzzwords 2024
End-to-end pipeline agility - Berlin Buzzwords 2024End-to-end pipeline agility - Berlin Buzzwords 2024
End-to-end pipeline agility - Berlin Buzzwords 2024
 
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
 
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
 
The Ipsos - AI - Monitor 2024 Report.pdf
The  Ipsos - AI - Monitor 2024 Report.pdfThe  Ipsos - AI - Monitor 2024 Report.pdf
The Ipsos - AI - Monitor 2024 Report.pdf
 
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataPredictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
 
Experts live - Improving user adoption with AI
Experts live - Improving user adoption with AIExperts live - Improving user adoption with AI
Experts live - Improving user adoption with AI
 

Sets automata

  • 1. Ajeela Mushtaq Roll NO:-13-Mcs-15 PRESENTED TO:-PRESENTED TO:- MR. MIR AADIL SETSSETS
  • 2. Introduction •Definition: A set is an unordered collection of (unique) objects. •Sets are fundamental discrete structures and for the basis of more complex discrete structures like graphs
  • 3. • Definition: The objects in a set are called elements or members of a set. A set is said to contain its elements. • Notation, for a set A: – x  A: x is an element of A – x  A: x is not an element of A
  • 4. Terminology • Definition: Two sets, A and B, are equal is they contain the same elements. We write A=B. • Example: – {2,3,5,7}={3,2,7,5}, because a set is unordered – Also, {2,3,5,7}={2,2,3,5,3,7} because a set contains unique elements – However, {2,3,5,7} {2,3}
  • 5. • The set-builder notation O={ x | (xZ)  (x=2k) for some kZ} reads: O is the set that contains all x such that x is an integer and x is even • A set is defined in intension when you give its set-builder notation O={ x | (xZ)  (0x8)  (x=2k) for some k  Z } • A set is defined in extension when you enumerate all the elements: O={0,2,4,6,8}
  • 6. Venn Diagram: Example • A set can be represented graphically using a Venn Diagram U a x y z A C B
  • 7. • A set that has no elements is called the empty set or null set and is denoted  • A set that has one element is called a singleton set. – For example: {a}, with brackets, is a singleton set – a, without brackets, is an element of the set {a} • Note the subtlety in   {} – The left-hand side is the empty set – The right hand-side is a singleton set, and a set containing a set
  • 8. • Definition: A is said to be a subset of B, and we write A  B, if and only if every element of A is also an element of B. • That is, we have the equivalence: A  B   x (x  A  x  B)
  • 9. • Definition: A set A that is a subset of a set B is called a proper subset if A  B. • That is there is an element xB such that xA. • We write: A  B, A  B
  • 10. • Sets can be elements of other sets. • Examples – S1 = {,{a},{b},{a,b},c} – S2={{1},{2,4,8},{3},{6},4,5,6}.
  • 11. • Definition: If there are exactly n distinct elements in a set S, with n a nonnegative integer, we say that: – S is a finite set, and – The cardinality of S is n. Notation: |S| = n. • Definition: A set that is not finite is said to be infinite
  • 12. • Examples – Let B = {x | (x100)  (x is prime)}, the cardinality of B is |B|=25 because there are 25 primes less than or equal to 100. – The cardinality of the empty set is ||=0 – The sets N, Z, Q, R are all infinite
  • 13. Equivalence • You may be asked to show that a set is – a subset of, – proper subset of, or – equal to another set. • To prove that A is a subset of B, use the equivalence discussed earlier A  B  x(xA  xB) – To prove that A  B it is enough to show that for an arbitrary (nonspecific) element x, xA implies that x is also in B. – Any proof method can be used. • To prove that A is a proper subset of B, you must prove – A is a subset of B and – x (xB)  (xA)
  • 14. • Finally to show that two sets are equal, it is sufficient to show independently (much like a biconditional) that – A  B and – B  A • Logically speaking, you must show the following quantified statements: (x (xA  xB))  (x (xB  xA)) we will see an example later..
  • 15. Power Set • Definition: The power set of a set S, denoted P(S), is the set of all subsets of S. • Examples – Let A={a,b,c}, P(A)={,{a},{b},{c},{a,b},{b,c}, {a,c},{a,b,c}} Let A={{a,b},c}, P(A)={,{{a,b}},{c}, {{a,b},c}} • Fact: Let S be a set such that |S|=n, then |P(S)| = 2n
  • 16. Set Operations • Arithmetic operators (+,-,  ,) can be used on pairs of numbers to give us new numbers • Similarly, set operators exist and act on two sets to give us new sets – Union – Intersection – Set difference – Set complement
  • 17. Set Operators: Union • Definition: The union of two sets A and B is the set that contains all elements in A, B, r both. We write: AB = { x | (a  A)  (b  B) } U A B
  • 18. Set Operators: Intersection • Definition: The intersection of two sets A and B is the set that contains all elements that are element of both A and B. We write: A  B = { x | (a  A)  (b  B) } U A B
  • 19. Disjoint Sets • Definition: Two sets are said to be disjoint if their intersection is the empty set: A  B =  U A B
  • 20. Set Difference • Definition: The difference of two sets A and B, denoted AB ($setminus$) or A−B, is the set containing those elements that are in A but not in B U A B
  • 21. Set Complement • Definition: The complement of a set A, denoted A ($bar$), consists of all elements not in A. That is the difference of the universal set and U: UA A= AC = {x | x  A } U A A
  • 22. Set Complement: Absolute & Relative • Given the Universe U, and A,B  U. • The (absolute) complement of A is A=UA • The (relative) complement of A in B is BAU AA U BA