discrete computational structures

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DISCRETE COMPUTATIONAL STRUCTURES. CSE 2353 Spring 2006 Final Slides. CSE 2353 OUTLINE. Sets Logic Proof Techniques Integers and Induction Relations and Posets Functions Counting Principles Boolean Algebra. Learning Objectives. Learn about functions - PowerPoint PPT Presentation

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DISCRETE COMPUTATIONAL STRUCTURES

CSE 2353

Spring 2006

Final Slides

CSE 2353 OUTLINE

1. Sets 2. Logic

3. Proof Techniques

4. Integers and Induction

5. Relations and Posets

6. Functions7. Counting Principles

8. Boolean Algebra

Discrete Mathematical Structures: Theory and Applications 3

Learning Objectives

Learn about functions

Explore various properties of functions

Learn about binary operations

Discrete Mathematical Structures: Theory and Applications 4

Functions

Discrete Mathematical Structures: Theory and Applications 5

Discrete Mathematical Structures: Theory and Applications 6

Discrete Mathematical Structures: Theory and Applications 7

Functions Every function is a relation

Therefore, functions on finite sets can be described by arrow diagrams. In the case of functions, the arrow diagram may be drawn slightly differently.

If f : A → B is a function from a finite set A into a finite set B, then in the arrow diagram, the elements of A are enclosed in ellipses rather than individual boxes.

Discrete Mathematical Structures: Theory and Applications 8

Functions

To determine from its arrow diagram whether a relation f from a set A into a set B is a function, two things are checked:

1) Check to see if there is an arrow from each element of A to an element of B

This would ensure that the domain of f is the set A, i.e., D(f) = A

2) Check to see that there is only one arrow from each element of A to an element of B

This would ensure that f is well defined

Discrete Mathematical Structures: Theory and Applications 9

Functions

Let A = {1,2,3,4} and B = {a, b, c , d} be sets

The arrow diagram in Figure 5.6 represents the relation f from A into B

Every element of A has some image in B

An element of A is related to only one element of B; i.e., for each a ∈ A there exists a unique element b ∈ B such that f (a) = b

Discrete Mathematical Structures: Theory and Applications 10

Functions

Therefore, f is a function from A into B

The image of f is the set Im(f) = {a, b, d}

There is an arrow originating from each element of A to an element of B D(f) = A

There is only one arrow from each element of A to an element of B f is well defined

Discrete Mathematical Structures: Theory and Applications 11

Functions

The arrow diagram in Figure 5.7 represents the relation g from A into B

Every element of A has some image in B D(g ) = A

For each a ∈ A, there exists a unique element b ∈ B such that g(a) = b g is a function from A into

B

Discrete Mathematical Structures: Theory and Applications 12

Functions

The image of g is Im(g) = {a, b, c , d} = B

There is only one arrow from each element of A to an element of B g is well defined

Discrete Mathematical Structures: Theory and Applications 13

Functions

Discrete Mathematical Structures: Theory and Applications 14

Functions

Discrete Mathematical Structures: Theory and Applications 15

Functions Let A = {1,2,3,4} and B = {a, b, c ,

d}. Let f : A → B be a function such that the arrow diagram of f is as shown in Figure 5.10

The arrows from a distinct element of A go to a distinct element of B. That is, every element of B has at most one arrow coming to it.

If a1, a2 ∈ A and a1 = a2, then f(a1) = f(a2). Hence, f is one-one.

Each element of B has an arrow coming to it. That is, each element of B has a preimage.

Im(f) = B. Hence, f is onto B. It also follows that f is a one-to-one correspondence.

Example 5.1.16

Discrete Mathematical Structures: Theory and Applications 16

Functions

Let A = {1,2,3,4} and B = {a, b, c , d, e}

f : 1 → a, 2 → a, 3 → a, 4 → a

For this function the images of distinct elements of the domain are not distinct. For example 1 2, but f(1) = a = f(2) .

Im(f) = {a} B. Hence, f is neither one-one nor onto B.

Example 5.1.18

Discrete Mathematical Structures: Theory and Applications 17

Functions Let A = {1,2,3,4} and

B = {a, b, c , d, e}

f : 1 → a, 2 → b, 3 → d, 4 → e

For this function, the images of distinct elements of the domain are distinct. Thus, f is one-one. In this function, for the element c of B, the codomain, there is no element x in the domain such that f(x) = c ; i.e., c has no preimage. Hence, f is not onto B.

Discrete Mathematical Structures: Theory and Applications 18

Functions

Discrete Mathematical Structures: Theory and Applications 19

Functions

Let A = {1,2,3,4}, B = {a, b, c , d, e},and C = {7,8,9}. Consider the functions f : A → B, g : B → C as defined by the arrow diagrams in Figure 5.14.

The arrow diagram in Figure 5.15 describes the function h = g ◦ f : A → C.

Discrete Mathematical Structures: Theory and Applications 20

Functions

Discrete Mathematical Structures: Theory and Applications 21

Functions

Discrete Mathematical Structures: Theory and Applications 22

Special Functions and Cardinality of a Set

Discrete Mathematical Structures: Theory and Applications 23

Special Functions and Cardinality of a Set

Discrete Mathematical Structures: Theory and Applications 24

Special Functions and Cardinality of a Set

Discrete Mathematical Structures: Theory and Applications 25

Special Functions and Cardinality of a Set

Discrete Mathematical Structures: Theory and Applications 26

Special Functions and Cardinality of a Set

Discrete Mathematical Structures: Theory and Applications 27

Special Functions and Cardinality of a Set

Discrete Mathematical Structures: Theory and Applications 28

Special Functions and Cardinality of a Set

Discrete Mathematical Structures: Theory and Applications 29

Special Functions and Cardinality of a Set

Discrete Mathematical Structures: Theory and Applications 30

Discrete Mathematical Structures: Theory and Applications 31

Special Functions and Cardinality of a Set

Discrete Mathematical Structures: Theory and Applications 32

Special Functions and Cardinality of a Set

Discrete Mathematical Structures: Theory and Applications 33

Special Functions and Cardinality of a Set

Discrete Mathematical Structures: Theory and Applications 34

Special Functions and Cardinality of a Set

Discrete Mathematical Structures: Theory and Applications 35

Discrete Mathematical Structures: Theory and Applications 36

Special Functions and Cardinality of a Set

Discrete Mathematical Structures: Theory and Applications 37

Binary Operations

Discrete Mathematical Structures: Theory and Applications 38

Discrete Mathematical Structures: Theory and Applications 39

Discrete Mathematical Structures: Theory and Applications 40

CSE 2353 OUTLINE

1. Sets 2. Logic

3. Proof Techniques

4. Integers and Induction

5. Relations and Posets

6. Functions

7. Counting Principles8. Boolean Algebra

Discrete Mathematical Structures: Theory and Applications 42

Learning Objectives

Learn the basic counting principles—multiplication and addition

Explore the pigeonhole principle

Learn about permutations

Learn about combinations

Discrete Mathematical Structures: Theory and Applications 43

Basic Counting Principles

Discrete Mathematical Structures: Theory and Applications 44

Basic Counting Principles

Discrete Mathematical Structures: Theory and Applications 45

Basic Counting Principles

Discrete Mathematical Structures: Theory and Applications 46

Pigeonhole Principle

The pigeonhole principle is also known as the Dirichlet drawer principle, or the shoebox principle.

Discrete Mathematical Structures: Theory and Applications 47

Pigeonhole Principle

Discrete Mathematical Structures: Theory and Applications 48

Discrete Mathematical Structures: Theory and Applications 49

Pigeonhole Principle

Discrete Mathematical Structures: Theory and Applications 50

Permutations

Discrete Mathematical Structures: Theory and Applications 51

Permutations

Discrete Mathematical Structures: Theory and Applications 52

Combinations

Discrete Mathematical Structures: Theory and Applications 53

Combinations

Discrete Mathematical Structures: Theory and Applications 54

Generalized Permutations and Combinations

Discrete Mathematical Structures: Theory and Applications 55

Generalized Permutations and Combinations

CSE 2353 OUTLINE

1. Sets 2. Logic

3. Proof Techniques

4. Integers and Induction

5. Relations and Posets

6. Functions

7. Counting Principles

8. Boolean Algebra

Discrete Mathematical Structures: Theory and Applications 57

Learning Objectives

Learn about Boolean expressions

Become aware of the basic properties of Boolean algebra

Explore the application of Boolean algebra in the design of electronic circuits

Learn the application of Boolean algebra in switching circuits

Discrete Mathematical Structures: Theory and Applications 58

Two-Element Boolean AlgebraLet B = {0, 1}.

Discrete Mathematical Structures: Theory and Applications 59

Two-Element Boolean Algebra

Discrete Mathematical Structures: Theory and Applications 60

Discrete Mathematical Structures: Theory and Applications 61

Discrete Mathematical Structures: Theory and Applications 62

Discrete Mathematical Structures: Theory and Applications 63

Two-Element Boolean Algebra

Discrete Mathematical Structures: Theory and Applications 64

Two-Element Boolean Algebra

Discrete Mathematical Structures: Theory and Applications 65

Discrete Mathematical Structures: Theory and Applications 66

Discrete Mathematical Structures: Theory and Applications 67

Discrete Mathematical Structures: Theory and Applications 68

Discrete Mathematical Structures: Theory and Applications 69

Discrete Mathematical Structures: Theory and Applications 70

Boolean Algebra

Discrete Mathematical Structures: Theory and Applications 71

Boolean Algebra

Discrete Mathematical Structures: Theory and Applications 72

Logical Gates and Combinatorial Circuits

Discrete Mathematical Structures: Theory and Applications 73

Logical Gates and Combinatorial Circuits

Discrete Mathematical Structures: Theory and Applications 74

Logical Gates and Combinatorial Circuits

Discrete Mathematical Structures: Theory and Applications 75

Logical Gates and Combinatorial Circuits

Discrete Mathematical Structures: Theory and Applications 76

Discrete Mathematical Structures: Theory and Applications 77

Discrete Mathematical Structures: Theory and Applications 78

Discrete Mathematical Structures: Theory and Applications 79

Discrete Mathematical Structures: Theory and Applications 80

Discrete Mathematical Structures: Theory and Applications 81

Discrete Mathematical Structures: Theory and Applications 82

Discrete Mathematical Structures: Theory and Applications 83

Discrete Mathematical Structures: Theory and Applications 84

Discrete Mathematical Structures: Theory and Applications 85

Discrete Mathematical Structures: Theory and Applications 86

Discrete Mathematical Structures: Theory and Applications 87

Logical Gates and Combinatorial Circuits

The Karnaugh map, or K-map for short, can be used to minimize a sum-of-product Boolean expression.

Discrete Mathematical Structures: Theory and Applications 88

Discrete Mathematical Structures: Theory and Applications 89

Discrete Mathematical Structures: Theory and Applications 90

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