Download presentation

Presentation is loading. Please wait.

Published byMiya Morland Modified about 1 year ago

1
CSCI 115 Chapter 6 Order Relations and Structures

2
CSCI 115 §6.1 Partially Ordered Sets

3
§6.1 – Partially Ordered Sets POSET –A relation R on a set A is called a partial order if R is reflexive, antisymmetric, and transitive. The set A together with the partial order R is called a partially ordered set or poset, and is denoted (A,R).

4
§6.1 – Partially Ordered Sets Dual Comparable Linear order (chain)

5
§6.1 – Partially Ordered Sets Theorem –If (A, 1 ) and (B, 2 ) are posets, then (A x B, ) is a poset where is defined by: (a, b) (a’, b’) iff a 1 a’ in A and b 2 b’ in B. (A x A, ) where 1 = 2 is called the product partial order

6
§6.1 – Partially Ordered Sets < –a < b if a b and a b Lexicographic (dictionary) order –Let (A, ) and (B, ) be posets. Then defined as (a, b) (a’, b’) iff a < a’ or a = a’ and b b’ is a partial order called the lexicographic or dictionary order.

7
§6.1 – Partially Ordered Sets Theorem –The digraph of a partial order has no cycle of length greater than 1

8
§6.1 – Partially Ordered Sets Hasse Diagram for (A, ) –i) Draw digraph of –ii) Delete all cycles of length 1 –iii) Delete all edges implied by transitive property –iv) Draw diagram with all edges pointing up and omit any arrows –v) Replace circles with labeled points Hasse diagram gives a visual representation with all the implied components removed

9
§6.1 – Partially Ordered Sets Topological Sorting –Linear order that is an extension of a partial order –Typical notation: –Many topological sortings may exist for a given partial order

10
§6.1 – Partially Ordered Sets Let (A, ) and (B, ) be posets. Let f:A B. f is called an isomorphism if: –i) f is a 1-1 correspondence –ii) a 1, a 2 A, a 1 a 2 iff f(a 1 ) f(a 2 ) In this case, we say (A, ) and (B, ) are isomorphic posets.

11
§6.1 – Partially Ordered Sets Theorem (Principle of correspondence) –Let (A, ) and (B, ) be finite posets and f:A B be a 1-1 correspondence. Let H be the Hasse diagram of (A, ). Then: i) If f is an isomorphism and each label a of H is replaced by f(a), then H becomes a Hasse diagram for (B, ). ii) If H becomes a Hasse diagram for (B, ) when each label a of H is replaced by f(a), then f is an isomorphism.

12
CSCI 115 §6.2 Extremal Elements of Partially Ordered Sets

13
§6.2 Extremal elements of posets Maximal Element –a A is a maximal element of (A,R) if there does not exist c A s.t. a < c Minimal Element –b A is a minimal element of (A,R) if there does not exist d A s.t. d < b Theorem –Let (A, ) be a poset with A finite and non-empty. Then A has at least one maximal element, and at least one minimal element.

14
§6.2 Extremal elements of posets Procedure to find a topological sorting of a finite poset (A, ≤) 1.Declare an array called SORT the size of |A| 2.Choose a minimal element x of A and remove x from A 3.Make x the next element in SORT 4.Repeat steps 2 – 3 until A = {}

15
§6.2 Extremal elements of posets Greatest Element (Unit Element: 1) –a A is a greatest element of (A,R) if x A x a. Least Element (Zero Element: 0) –b A is a least element of (A,R) if x A b x. Theorem –A poset has at most one greatest element, and at most one least element.

16
§6.2 Extremal elements of posets Let (A, ) be a poset, with B A. –Upper Bound (UB) a A is an upper bound of B if b a b B. –Least Upper Bound (LUB) a A is a least upper bound of B if a is an upper bound for B, and a a’ whenever a’ is an upper bound of B. –Lower Bound (LB) a A is a lower bound of B if a b b B. –Greatest Lower Bound (GLB) a A is a greatest lower bound of B if a is a lower bound for B, and a’ a whenever a’ is a lower bound of B.

17
§6.2 Extremal elements of posets Theorem –Let (A, ) be a poset. Then a subset B of A has at most one LUB and at most one GLB.

18
§6.2 Extremal elements of posets Theorem –Suppose (A, ) and (B, ) are isomorphic posets under f:A B. Then: i) If a is a max (min) element of (A, ), then f(a) is a max (min) element of (B, ). ii) If a is a greatest (least) element of (A, ), then f(a) is a greatest (least) element of (B, ). iii) If a is an UB (LB, LUB, GLB) of (A, ), then f(a) is an UB (LB, LUB, GLB) of (B, ). iv) If every subset of (A, ) has a LUB (GLB), then every subset of (B, ) has a LUB (GLB).

19
CSCI 115 §6.3 Lattices

20
§6.3 – Lattices Lattice –Poset (L, ) where every subset of 2 elements has a LUB and GLB –Join of 2 elements a b = LUB ({a, b}) –Meet of 2 elements a b = GLB ({a, b})

21
§6.3 – Lattices Theorem –If (L 1, 1 ) and (L 2, 2 ) are lattices, then (L, ) is a lattice where L = L 1 x L 2 and is the product partial order Let (L, ) be a lattice. A non-empty subset S of L is called a sublattice of L if a b S and a b S a, b S

22
§6.3 – Lattices Isomorphic Lattices –If f:L 1 L 2 is an isomorphism from the poset (L 1, 1 ) to the poset (L 2, 2 ), and if L 1 and L 2 are Lattices, then L 1 and L 2 are isomorphic lattices.

23
§6.3 – Lattices Theorem –Let L be a lattice. a, b L we have: i) a b = b iff a b ii) a b = a iff a b iii) a b = a iff a b = b Theorem – in book We will not cover special types of lattices –Bounded, distributive, complemented

24
CSCI 115 §6.4 Finite Boolean Algebras

25
§6.4 – Finite Boolean Algebras Theorem –If S 1 = {x 1, x 2, …, x n } and S 2 = {y 1, y 2, …, y n } are 2 finite sets with n elements, then the lattices (P(S 1 ), ) and (P(S 2 ), ) are isomorphic lattices. Consequently, the Hasse diagram of these lattices may be drawn identically.

26
§6.4 – Finite Boolean Algebras If the Hasse diagram of a lattice corresponding to a set with n elements is labeled by a sequence of 0s and 1s of length n, then the resulting lattice is called B n.

27
§6.4 – Finite Boolean Algebras If x = a 1 a 2 … a n and y = b 1 b 2 … b n are 2 elements of B n, then the properties of B n can be described by: –i) x y iff a k b k for k = 1, 2, 3, …, n –ii) x y = c 1 c 2 … c n where c k = min{a k, b k } –iii) x y = d 1 d 2 … d n where d k = max{a k, b k }

28
§6.4 – Finite Boolean Algebras A finite lattice is called a Boolean Algebra if it is isomorphic to B n for some n Z + Theorem (modified) –D n is a boolean algebra iff n = p 1 p 2 … p k where the p i are all distinct primes Theorem and in book

29
CSCI 115 §6.5 Functions on Boolean Algebras

30
§6.5 – Fns on Boolean Algebras Boolean Polynomials –Let x 1, x 2, …, x n be a set of n variables. A Boolean Polynomial p(x 1, x 2, …, x n ) in the variables x k is defined by the following: i) x 1, x 2, …, x n are all boolean polynomials ii) 0 and 1 are boolean polynomials iii) If p(x 1, x 2, …, x n ) and q(x 1, x 2, …, x n ) are both boolean polynomials in the variables x k, then p(x 1, x 2, …, x n ) q(x 1, x 2, …, x n ) and p(x 1, x 2, …, x n ) q(x 1, x 2, …, x n ) are also boolean polynomials iv) If p(x 1, x 2, …, x n ) is a boolean polynomial, then so is If p(x 1, x 2, …, x n )’ v) Only polynomials generated by rules 1 – 4 are boolean polynomials

31
§6.5 – Fns on Boolean Algebras Manipulations –Not responsible for manipulations Boolean Functions –Similar to polynomial functions Accept arguments, and return values Evaluates to true or false

32
§6.5 – Fns on Boolean Algebras Schematic representations of boolean polynomials –Used in circuitry, and other technical areas –AND gates –OR gates –NOT inverters

33
§6.5 – Fns on Boolean Algebras The AND gate –Accepts 2 arguments, and evaluates to true or false according to the logical rules for AND

34
§6.5 – Fns on Boolean Algebras The OR gate –Accepts 2 arguments, and evaluates to true or false according to the logical rules for OR

35
§6.5 – Fns on Boolean Algebras The NOT inverter –Accepts 1 argument, and evaluates to true or false according to the logical rules for NOT

Similar presentations

© 2016 SlidePlayer.com Inc.

All rights reserved.

Ads by Google