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DISCRETE COMPUTATIONAL STRUCTURES

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

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DISCRETE COMPUTATIONAL STRUCTURES

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  1. DISCRETE COMPUTATIONAL STRUCTURES CSE 2353 Spring 2006 Final Slides

  2. CSE 2353 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 Ainto 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 5.1.16 • 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 Example 5.1.18 • 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. 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. Discrete Mathematical Structures: Theory and Applications

  41. CSE 2353 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

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