Discrete Structures & Algorithms Basics of Set Theory - PowerPoint PPT Presentation

bernad
discrete structures algorithms basics of set theory n.
Skip this Video
Loading SlideShow in 5 Seconds..
Discrete Structures & Algorithms Basics of Set Theory PowerPoint Presentation
Download Presentation
Discrete Structures & Algorithms Basics of Set Theory

play fullscreen
1 / 33
Download Presentation
Discrete Structures & Algorithms Basics of Set Theory
381 Views
Download Presentation

Discrete Structures & Algorithms Basics of Set Theory

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. Discrete Structures & AlgorithmsBasics of Set Theory EECE 320 — UBC

  2. Set Theory: Definitions and notation A set is an unordered collection of elements. Some examples • {1, 2, 3} is the set containing “1” and “2” and “3.” • {1, 1, 2, 3, 3} = {1, 2, 3} since repetition is irrelevant. • {1, 2, 3} = {3, 2, 1} since sets are unordered. • {1, 2, 3, …} is a way we denote an infinite set (in this case, the natural numbers). •  = {} is the empty set, or the set containing no elements. Note:   {}

  3. A B Definitions and notation x  S means “x is an element of set S.” x  S means “x is not an element of set S.” A  B means “A is a subset of B.” or, “B contains A.” or, “every element of A is also in B.” or, x ((x  A)  (x  B)). Venn Diagram

  4. Definitions and notation A  B means “A is a subset of B.” A  B means “A is a superset of B.” A = B if and only if A and B have exactly the same elements. iff, A  B and B  A iff, A  B and A  B iff, x ((x  A)  (x  B)). • So to show equality of sets A and B, show: • A  B • B  A

  5. A B Definitions and notation A  B means “A is a proper subset of B.” • A  B, and A  B. • x ((x  A)  (x  B))  x ((x  B)  (x  A)) • x ((x  A)  (x  B))  x ((x  B) v (x  A)) • x ((x  A)  (x  B)) x ((x  B) (x  A)) • x ((x  A)  (x  B)) x ((x  B)  (x  A))

  6. Definitions and notation Quick examples: • {1,2,3}  {1,2,3,4,5} • {1,2,3}  {1,2,3,4,5} Is   {1,2,3}? Yes!x (x  )  (x  {1,2,3}) holds, because (x  ) is false. Vacuously Is   {1,2,3}? No! Is   {,1,2,3}? Yes!

  7. Yes Yes Yes No Definitions and notation Quiz Time Is {x}  {x}? Is {x}  {x,{x}}? Is {x}  {x,{x}}? Is {x}  {x}?

  8. : and | are read “such that” or “where” Primes How to specify sets • Explicitly: {John, Paul, George, Ringo} • Implicitly: {1,2,3,…}, or {2,3,5,7,11,13,17,…} • Set builder: { x : x is prime }, { x | x is odd }. In general { x : P(x) is true }, where P(x) is some description of the set. Example: Let D(x,y) denote “x is divisible by y.” Give another name for { x : y ((y > 1)  (y < x)) D(x,y) }. Can we use any predicate P to define a set S = { x : P(x) }?

  9. Doh! So S must not be in S, right? No! Who shaves the barber? Predicates for defining sets Can we use anypredicate P to define a set S = { x : P(x) }? Define S = { x : x is a set where x  x } Then, if S  S, then by the definition of S, S  S. But, if S  S, then by the definition of S, S  S. There is a town with a barber who shaves all the people (and only the people) who do not shave themselves.

  10. Cardinality of sets If S is finite, then the cardinality of S, |S|, is the number of distinct elements in S. If S = {1,2,3}, |S| = 3. If S = {3,3,3,3,3}, |S| = 1. If S = , |S| = 0. |S| = 3. If S = { , {}, {,{}} }, If S = {0,1,2,3,…}, |S| is infinite. (more on this later)

  11. Power sets If S is a set, then the power set of S is 2S = { x : x  S }. or P(S) We say, “P(S) is the set of all subsets of S.” 2S = {, {a}}. If S = {a}, If S = {a,b}, 2S = {, {a}, {b}, {a,b}}. 2S = {}. If S = , 2S = {, {}, {{}}, {,{}}}. If S = {,{}}, Fact: if S is finite, |2S| = 2|S|. (If |S| = n, |2S| = 2n.)

  12. Cartesian product The Cartesian product of two sets A and B is: A x B = { <a,b> : a  A  b  B} We’ll use these special sets soon! If A = {Charlie, Lucy, Linus}, and B = {Brown, VanPelt}, then A x B = {<Charlie, Brown>, <Lucy, Brown>, <Linus, Brown>, <Charlie, VanPelt>, <Lucy, VanPelt>, <Linus, VanPelt>} A1 x A2 x … x An = {<a1, a2,…, an>: a1  A1, a2  A2, …, an  An} AxB |A|+|B| |A+B| |A||B| A,B finite  |AxB| = ?

  13. B A Operators The union of two sets A and B is: A  B = { x : x  A v x  B} If A = {Charlie, Lucy, Linus}, and B = {Lucy, Desi}, then A  B = {Charlie, Lucy, Linus, Desi}

  14. B A Operators The intersection of two sets A and B is: A  B = { x : x  A  x  B} If A = {Charlie, Lucy, Linus}, and B = {Lucy, Desi}, then A  B = {Lucy}

  15. Operators The intersection of two sets A and B is: A  B = { x : x  A  x  B} If A = {x : x is a US president}, and B = {x : x is deceased}, then A  B = {x : x is a deceased US president} B A

  16. B A Sets whose intersection is empty are called disjoint sets Operators The intersection of two sets A and B is: A  B = { x : x  A  x  B} If A = {x : x is a US president}, and B = {x : x is in this room}, then A  B = {x : x is a US president in this room} = 

  17. A Operators The complement of a set A is Ac = { x : x  A} If A = {x : x is bored}, then A = {x : x is not bored} =  U • c = U and Uc = 

  18. U A B Operators The set difference, A - B, is: A - B = { x : x  A  x  B } A - B = A  Bc

  19. U A B like “exclusive or” Operators The symmetric difference, A  B, is: A  B = { x : (x  A  x  B) v (x  B  x  A)} = (A - B) U (B - A)

  20. Operators A  B = { x : (x  A  x  B) v (x  B  x  A)} = (A - B) U (B - A) Proof: { x : (x  A  x  B) v (x  B  x  A)} = { x : (x  A - B) v (x  B - A)} = { x : x  ((A - B) U (B - A))} = (A - B) U (B - A)

  21. Famous identities • Two pages of (almost) obvious equivalences. • One page of HS algebra. • Some new material? Don’t memorize them, understand them! They’re in Rosen, Sec. 2.2

  22. A  U = A A U U = U A U A = A A U  = A A  =  A A = A Identities • Identity • Domination • Idempotent

  23. A U A = U A = A A A= Identities • Excluded middle • Uniqueness • Double complement

  24. B U A B  A A U (B U C) A U (B C) = A  (B C) A  (B U C) = Identities • Commutativity • Associativity • Distributivity A U B = A  B = (A U B)U C = (A  B) C = (A U B)  (A U C) (A  B) U (A  C)

  25. Identities • DeMorgan’s Law I • DeMorgan’s Law II (A UB)c= Ac  Bc (A  B)c= Ac U Bc Hand waving is good for intuition, but we aim for a more formal proof. p q

  26. New & important Like truth tables Like  Not hard, a little tedious Proving identities • Show that A  B and that A  B. • Use a membership table. • Use previously proven identities. • Use logical equivalences to prove equivalent set definitions.

  27. Proving identities (1) Prove that • () (x  (A U B)c)  (x  A U B)  (x  A and x  B)  (x  Ac  Bc) • () (x  Ac  Bc)  (x  A and x  B)  (x  A U B)  (x  (A U B)c) (A UB)c= Ac  Bc

  28. Proving identities (2) Prove that (A UB)c= Ac  Bc using a membership table. 0 : x is not in the specified set 1 : otherwise Have we not seen this before?

  29. (A UB)= A U B = A  B = A  B Proving identities (3) Prove that (A UB)c= Ac  Bc using identities.

  30. Proving identities (4) Prove that (A UB)c= Ac  Bc using logically equivalent set definitions. (A UB)c= {x : (x  A v x  B)} = {x : (x  A)  (x  B)} = {x : (x  Ac)  (x  Bc)} = Ac  Bc

  31. A proof to do X  (Y - Z) = (X  Y) - (X  Z). True or False? Prove your response. (X  Y) - (X  Z) = (X  Y)  (X  Z)’ = (X  Y)  (X’ U Z’) = (X  Y  X’) U (X  Y  Z’) =  U (X  Y  Z’) = (X  Y  Z’)

  32. Another proof to do Prove that if (A - B) U (B - A) = (A U B) then ______ A  B =  A U B =  A = B A  B =  A-B = B-A =  Suppose to the contrary, that A  B  , and that x  A  B. Then x cannot be in A-B and x cannot be in B-A. DeMorgan’s Law Then x is not in (A - B) U (B - A). Do you see the contradiction yet? But x is in A U B since (A  B)  (A U B). Trying to prove p  q Assume p and not q, and find a contradiction. Our contradiction was that sets were not equal. Thus, A  B = .

  33. Wrap up • Sets are an essential structure for all mathematics. • We covered the basic definitions and identities that will allow us to reason about sets.