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DISCRETE COMPUTATIONAL STRUCTURES

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Presentation on theme: "DISCRETE COMPUTATIONAL STRUCTURES"— Presentation transcript:

1 DISCRETE COMPUTATIONAL STRUCTURES
CSE 2353 Spring 2006 Final Slides

2 Integers and Induction
CSE OUTLINE Sets Logic Proof Techniques Integers and Induction Relations and Posets Functions Counting Principles Boolean Algebra

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: 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 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 Example 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. Discrete Mathematical Structures: Theory and Applications

16 Functions Let A = {1,2,3,4} and B = {a, b, c , d, e}
Example Let A = {1,2,3,4} and B = {a, b, c , d, e} f : 1 → a, 2 → a, 3 → a, → 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. 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, → 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 Discrete Mathematical Structures: Theory and Applications

41 Integers and Induction
CSE OUTLINE Sets Logic Proof Techniques Integers and Induction Relations and Posets Functions Counting Principles Boolean Algebra

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
Discrete Mathematical Structures: Theory and Applications

56 Integers and Induction
CSE OUTLINE Sets Logic Proof Techniques Integers and Induction Relations and Posets Functions Counting Principles Boolean Algebra

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 Algebra
Let 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 Discrete Mathematical Structures: Theory and Applications


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