1 / 41

Lesson 15: Rela tions a nd algebr as

Lesson 15: Rela tions a nd algebr as. Compile d by : Ondřej Kohut (within the Theory of formal systems course). Contents. T heory of sets ( revision ) Rela tions a nd mappings ( revision ) Relations Binar y relations on a set Mappings Partitions, equivalence s Orderings

kiethc
Download Presentation

Lesson 15: Rela tions a nd algebr as

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Lesson 15:Relations and algebras Compiled by: Ondřej Kohut (within the Theory of formal systems course)

  2. Contents • Theory of sets (revision) • Relations andmappings (revision) • Relations • Binary relations on a set • Mappings • Partitions, equivalences • Orderings • Algebras • Algebraswith oneoperation • Algebraswith twooperations • Lattices Relace a algebry

  3. Naive theory of sets • Language: • Special symbols: • Binary predicates:  (is an element of),  (is a proper subset of),  (is a subset of) • Binary function symbols:  (intersection),  (union) • Cantor – the naive set theory (without axiomatization) • There are many formal axiomatizations, but none of them is complete. • Examples: von Neumann-Bernays-Gödel, Zermelo-Fränkel + axiom of choice Relace a algebry

  4. Zermelo-Fränkel set-theory Axiom of extensionality: Two sets are the same if and only if they have the same elements. Axiom of empty set: There is a set with no elements. Axiom of pairing: If x, y are sets, then so is {x,y}, a set containing x and y as its only elements. Axiom of union: Every set has a union. That is, for any set x there is a set y whose elements are precisely the elements of the elements of x. Axiom of infinity: There exists a set x such that {} is in x and whenever y is in x, so is the union y U {y}. Axiom of separation (or subset axiom): Given any set and any proposition P(x), there is a subset of the original set containing precisely those elements x for which P(x) holds. Axiom of replacement: Given any set and any mapping, formally defined as a proposition P(x,y) where P(x,y) and P(x,z) implies y = z, there is a set containing precisely the images of the original set's elements. Axiom of power set: Every set has a power set. That is, for any set x there exists a set y, such that the elements of y are precisely the subsets of x. Axiom of regularity (or axiom of foundation): Every non-empty set x contains some element y such that x and y are disjoint sets. Axiom of choice: (Zermelo's version) Given a set x of mutually disjoint nonempty sets, there is a set y (a choice set for x) containing exactly one element from each member of x. Relace a algebry

  5. Naive theory of sets • Ø – an empty set • Cardinality of a set A: |A| Relations between sets (axioms): • Equality • Inclusion Relace a algebry

  6. Naive theory of sets – set theoretical operations • Intersection • Union • Difference • Symetrical difference • Complement with respect to universe U Relace a algebry

  7. Naive theory of sets – set theoretical operations • Potential set • Cartesian product • Cartesian power A1=A, A0={Ø} n Relace a algebry

  8. Relations • n-ary relation between the sets A1, A2, ..., An • Examples: • D = a set of possible days • M = a set of VŠB rooms • Z = a set of VŠB employees A ternary relation meeting (when, where, who): Relace a algebry

  9. Binary relations • Inverse relation to r: • Composition of relations Relace a algebry

  10. Binary relations A binary relation r on a set A is called: • Reflexive: x A: (x,x) r • Irreflexive: x A: (x,x) r • Symmetric: x,y A: (x,y) r (y,x) r • Antisymmetric: x,y A: (x,y) r and(y,x) r x=y • Asymmetric: x,y A: (x,y) r (y,x) r • Transitive: x,y,z A: (x,y) r and(y,z) r (x,z) r • Cyclic: x,y,z A: (x,y) r and(y,z) r (z,x) r • Linear: x,y A: x=y or (x,y) ror (y,x) r Relace a algebry

  11. Binary relations The important types of binary relations: • Tolerance – reflexive, symmetric • Quasi-ordering – reflexive, transitive • Equivalence – reflexive, symmetric, transitive • Partial ordering – reflexive, antisymmetric, transitive Relace a algebry

  12. Binary relations Examples: • Tolerance: • „to be akin to“ on a set of people, • „to have a different age no more than one year“ on the set of people, ... • Quasi-ordering: • „if it holds |X||Y|, then sets X and Y are in relation“ on a set of sets, • divisibility relation on a set of integers, • „not to be older“ on the set of people, ... • Equivalence: • „to be the same age“ on the set of people, • equivalence on a set of natural numbers, ... • Ordering: • inclusion relation, • divisibility relation on the set of natural numbers, ... Relace a algebry

  13. Mappings (functions) • f A  B is called a mappingfrom a set A into a set B (partial mapping), iff: (x A, y1,y2B) ( (x,y1) f and(x,y2) f y1 = y2) • f is called amapping of a set A into a set B (total mapping,written as:f: AB), iff: • f is mapping from A to B • (x A)(y A) ( (x,y) f) • If f is a mapping and (x,y) f, then we write:f(x)=y Relace a algebry

  14. Mapping (functions) • Examples: u = {(x,y)ZZ; x=y2}, v = {(x,y)NN; x=y2}, w = {(x,y)ZZ; y=x2} • r, u – are not mappings • s, v – are partial mappings from A to B, (not total mappings) • t, w – are total mappings r A  B s A  B t A  B Relace a algebry

  15. Mapping (functions) Mapping f: AB is called • Injection (one to onemapping A intoB), iff: x1,x2A, y B: (x1,y) f and(x2,y) f x1 = x2 • Surjection (mapping A ontoB), iff: y B xA: (x,y) f • Bijection (one to onemapping A ontoB)(mutually single-valued), iff it is an injection and surjection. Relace a algebry

  16. Mapping (functions) • Examples: j: ZZ, j(n)=n2, k: ZN, k(n)=|n|, l: NN, l(n)=n+1,m: RR, j(x)=x3 • f, j – is neither an injection nor a surjection • h, k – are surjections, but not injections • g, l – are injections, but not surjections • I,m – is an injection and a surjection bijections f: A  B g: A  B h: A  B i: A  B Relace a algebry

  17. Partitions and equivalences • Partition on a set A is such a system that:X = {Xi; i  I } • Xi A pro i  I • XiXj = Ø pro i,j  I, i  j • U X = A Xi – classes of the partition • Refininment of a partition X = {Xi; i  I } is a system that: Y = {Yj; j  J }, iff: • j  J, i  I so that Yj Xi Relace a algebry

  18. Partitions and equivalences • Let r be an equivalence relation on a set A, X is a partition on A, then it holds: • Xr = {[x]r; xA} – the partition on A (the partition induced by equivalence r, the factor setof the set A according to the equivalence r) • rX = {(x,y); x and y belongs to the same class of the partition X} – equivalence on A (induced by partition X) Examples: • r ZZ; r = {(x,y); 3 divides x-y}  X={X1, X2, X3} • X1={…-6, -3, 0, 3, 6, …} • X2={…-5, -2, 1, 4, 7, …} • X3={…-4, -1, 2, 5, 8, …} Relace a algebry

  19. Orderings • If r is an order relation on A, then a couple (A,r) is called an ordered set • Written as: (A, ) • Examples: (N, ), (2M, ) • Coverrelation Let (A, ) be an ordered set, (a,b)A a –< b („b covers a“), iff: a < b and c A: a  c a c  b • Examples: (N, ), –< ={(n,n+1); n  N} Relace a algebry

  20. Orderings • Hasse diagram –graphicalpicturing • Example: (A, ), A={a,b,c,d,e} r = {(a,b), (a,c), (a,d), (b,d)}idA idA={(a,a): aA} Relace a algebry

  21. Orderings An element a of an ordered set (A, ) is called: • The least: for xA: a  x • The greatest: for xA: x  a • Minimal: for xA: (x  a  x = a) • Maximal: for xA: (a  x  x = a) • Examples: • The least: does not exist • The greatest: does not exist • Minimal: a, e • Maximal: d, c, e Relace a algebry

  22. Orderings • A mapping of the ordered sets (A, ), (B, ) is called isomorphic, iff the bijection f: AB exists such that: x,yA: x  y, iff f(x)  f(y) • A mapping of the ordered sets (A, ), (B, ) is called isotonef: AB, when it holds: x,yA: x  y  f(x)  f(y) • Examples: • f: NZ, f(x)=kx, k Z, k  0 is isotone • g: NZ, g(x)=kx, k Z, k  0 is not isotone Relace a algebry

  23. Orderings • Let(A, ) be an ordered set, M  A, then • LA(M)={x A;mM: x  m} • A set of lower bounds • UA(M)={x A;mM: m  x} • A set of upper bounds • InfA(M) – The greatest element of the set LA(M) • Infimum of the set M • SupA(M) – The least element of the set UA(M) • Supremum of the set M Relace a algebry

  24. Lattices - lattice ordered sets • A set(A, ) is called a lattice (lattice ordered set), iff: x,yA s,i A : s = sup({x,y}), i = inf({x,y}) • Notation: • x  y = sup({x,y}) • x  y = inf({x,y}) • If sup(M) a inf(M) exist for everyM  A, then (A, ) is called a complete lattice Relace a algebry

  25. Algebras Algebra (abstract algebra) is couple: (A, FA): • A Ø – an underlying set of algebra • FA = {fi: Ap(fi)A; iI} – a set of operations on A • p(fi) – an arity of operation fi • Examples: • (N, +2,2) the set of natural numbers with the addition and multiplication operations • (2M, , )the set of all subsets of a set M with the intersection and union operations • (F, , ) The set (F) of the propositional logic formulas with the conjunction and disjunction operations Relace a algebry

  26. Algebras with one binary operation Grupoid G=(G,) • : G  G  G • If a set G is finite, then the grupoid G is called finite • Order of a grupoid = |G| Examples of grupoids: • G1=(R,+), G2=(R,), G3=(N,+) ... Relace a algebry

  27. Algebras with one binary operation • We can express the finite grupoid G=(G,) byCayley table • Example: • G = {a,b,c} • For example: a  b = b, b  a = a, c  c = b ... Relace a algebry

  28. Algebras with one binary operation Let G=(G,) is grupoid, G is called: • Commutative, if it holds: • (a,bG)(a  b = b  a) • Associative, if it holds: • (a,b,cG)((a  b)  c = a  (b  c)) • With a neutral element, if it holds: • (e G aG)(a  e = a = e  a) • With an aggressive element, if it holds: • (o G aG)(a  o = o = o  a) • With inverse elements, if it holds: • (aG b G)(a  b = e = b  a) Relace a algebry

  29. Algebras with one binary operation Examples: • (R,), (N,+) – commutative and associative • (R,), a  b = (a+b) / 2 – commutative, not associative • (R,), a  b = ab– neither commutative nor associative • (R,) – 1 = the neutral element, 0 = the aggressive element Relace a algebry

  30. Algebras with one binary operation Let G=(G,G) be a grupoid. HG is called closed (with respect to the operation G), if it holds: • (a,bH)(a Gb H) A Grupoid H=(H,H) is a subgrupoid of a grupoid G=(G,G), if it holds: • Ø  H  G is closed • a,bH: a Hb = a Gb • Examples: • (N,+N) is a subgrupoid of (Z,+Z) • {0,1,2} is not the base set of a podgrupoid (Z,+Z) Relace a algebry

  31. Algebras with one binary operation • Let G1=(G1, 1), G2=(G2, 2) be a grupoids. • G1 G2 =(G1 G2, ) – direct product G1 andG2, where: • (a1, a2)  (b1, b2) = (a1 1b1, a2 2b2) Examples: • G1=(Z,+), G2=(Z,). • G1 G2 =(Z Z, ), • (a1, a2)  (b1, b2) = (a1 + b1, a2 b2) • (1,2)(3,4) = (1+3, 2  4) = (4,8) and so on. Relace a algebry

  32. Algebras with one binary operation • Let G =(G, G), H =(H, H) be grupoids and h:GHbe a mapping. • h is called homomorphism of grupoid G into grupoid H, if it holds: • a,bG: h(a Gb) = h(a) Hh(b) The types of homomorphism: • Monomorphism – h is injective • Epimorphism – h is surjective • Isomorphism – h is bijective • Endomorphism – H=G • Automorphism – is bijective and H=G Examples: • (R,+), h(x)= -x , h is automorfismus (R,+) into itself • h(x+y) = -(x+y) = (-x) + (-y) = h(x) + h(y) Relace a algebry

  33. Algebras with one binary operation r is called a congruence on a grupoid G=(G,G), iff: • r is a binary relation: θ GG • r is an equivalence • (a1, a2), (b1, b2)  r  (a1 Gb1, a2 Gb2)  r A factor grupoid of grupoid G according to the congruence r: G/r=(G/r,G/r), [a]rG/r[b]r = [a Gb]r Examples: • r ZZ; r = {(x,y); 3 divides x-y} • r is a congruence on (Z,+) Relace a algebry

  34. Algebras with one binary operation The types of grupoids: • Semigroup – an associative grupoid • Monoid – a semigroupwith the neutral element • Group – a monoid with the inverse elements • Abelian group– a commutative group Examples: • (Z, –) – grupoid, not a semigroup • (N – {0}, +) – semigroup, not a monoid • (N,) – monoid, not a group • (Z, +) – Abelian group Relace a algebry

  35. Algebras with two binary operation Algebra (A,+,·) is called a Ring, if it holds: • (A,+) is commutative group • (A,·) is monoid • For a,b,cA it holds: a·(b+c)=a·b+a·c, (b+c)·a=b·a + c·a • If |A|>1, then (A,+,·) is called a non-trivial ring. • Let 0 A is the neutral element of group (A,+). Then 0 is called the ring zero (A,+,·). • Let 1A is the neutral element of monoid (A,·). Then 1 is called the ringunit (A,+,·). Relace a algebry

  36. Algebras with two binary operation A ring (A,+,·) is called afield, if it holds: • (A - {0},·) is a commutative group Examples: • (Z,+,·) – a ring, not a field • (R,+,·),  (C,+,·) – fields Relace a algebry

  37. Lattice – algebraic structure • Lattice L = (L, , ) • : L  LL, : L  LL • x, y, z  L it holds: Relace a algebry

  38. Lattice – algebraic structure Let (A, , ) be a lattice, (B, ) be a lattice ordered set • Let us define a relation  on A : a b, iff a  b = b • Let us define the relations  and  on B a b = sup{a,b}, a b = inf{a,b}, Then itholds: • (A, ) is a lattice ordered set, where: sup{a,b}= a  b, inf{a,b}= a  b • (B, , ) is a lattice • (A, , ) = (A, , ) Relace a algebry

  39. Lattice – algebraic structure A lattice (L, , ) is called: • Modular, if it holds: x, y, z  L : x  z x  (y  z) = (x  y)  z • Distributive, if it holds: x, y, z  L : x  (y  z) = (x  y)  (x  z) x  (y  z) = (x  y)  (x  z) • Complementary, if it holds: : There is the least element 0  L and the greatest element 1  L x  L x’  L : x  x’ = 0, x  x’= 1 x’ iscalled a complement of an element x Relace a algebry

  40. Lattice – algebraic structure • Each distributive lattice is modular Examples: • M5 (diamond) – a modular lattice which is not distributive • N5 (pentagon) – is not modular M5 N5 Relace a algebry

  41. Lattice – algebraic structure Lattice (L, , ) is called Boolean lattice, when it is: • Complementary, distributive, with the least element 0  L and with thegreatest element 1  L Boolean algebra: • (L, , , –, 0, 1), – : LL is an operation of complement in L Example: • (2A, , ), A = {1,2,3,4,5,6,7} Relace a algebry

More Related