Properties of Relations In many applications to computer science and applied mathematics, we deal...

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Properties of Relations In many applications to computer science and applied mathematics, we deal with relations on a set A rather than relations from A to B A relation R on a set A is reflexive if (a,a)R for all aA; it’s irreflexive if (a,a)R for all aA • Let ={(a,a)| aA}, is the relation of equality on the set A, and is reflexive The matrix of a reflexive relation must have all 1’s on its main diagonal, while irreflexive must have all 0’s on its main diagonal. A reflexive relation has a cycle of length 1 at every vertex, while irreflexive has no cycles of length 1. R is reflexive if and only if R, and R is irreflexive if and only if R= • If R is reflexive on a set A, then Dom(R)=Ran(R)=A.

Transcript of Properties of Relations In many applications to computer science and applied mathematics, we deal...

Page 1: Properties of Relations In many applications to computer science and applied mathematics, we deal with relations on a set A rather than relations from.

Properties of Relations• In many applications to computer science and applied

mathematics, we deal with relations on a set A rather than relations from A to B

• A relation R on a set A is reflexive if (a,a)R for all aA; it’s irreflexive if (a,a)R for all aA

• Let ={(a,a)| aA}, is the relation of equality on the set A, and is reflexive

• The matrix of a reflexive relation must have all 1’s on its main diagonal, while irreflexive must have all 0’s on its main diagonal.

• A reflexive relation has a cycle of length 1 at every vertex, while irreflexive has no cycles of length 1.

• R is reflexive if and only if R, and R is irreflexive if and only if R=

• If R is reflexive on a set A, then Dom(R)=Ran(R)=A.

Page 2: Properties of Relations In many applications to computer science and applied mathematics, we deal with relations on a set A rather than relations from.

Symmetric, Asymmetric and Antisymmetric Relations

• A relation R on a set A is symmetric if whenever aRb, then bRa– R is not symmetric if there are some a and bA with

aRb, but bRa • A relation R on a set A is asymmetric if

whenever aRb, then bRa– R is not asymmetric if there are some a and bA

with both aRb and bRa• A relation R on a set A is antisymmetric if

whenever aRb and bRa, then a=b; – The contrapositive of this definition: R is

antisymmetric if whenever ab, then aRb or bRa– R is not antisymmetric if there are some a and bA,

ab, and both aRb and bRa

Page 3: Properties of Relations In many applications to computer science and applied mathematics, we deal with relations on a set A rather than relations from.

Symmetric, Asymmetric and Antisymmetric Relations

• MR =[mij] of a symmetric relation satisfies the property that if mij=1, then mji=1 and if mij=0, then mji=0; it’s a symmetric matrix– mii can be either 0 or 1 for all i

• MR =[mij] of an asymmetric relation satisfies the property that if mij=1, then mji=0 and mii=0 for all i– If mij=0, then mji can be either 0 or 1

• MR =[mij] of an antisymmetric relation satisfies the property that if ij, then mij=0, or mji=0– mii can be either 0 or 1 for all i

Page 4: Properties of Relations In many applications to computer science and applied mathematics, we deal with relations on a set A rather than relations from.

Symmetric, Asymmetric and Antisymmetric Relations

• If relation R is asymmetric, then the digraph of R cannot simultaneously have an edge from vertex i to j and an edge from j to i; and there can be no cycles of length 1: all edges are one-way

• If relation R is antisymmetric, then for different vertices i and j there cannot not be an edge from i to j and an edge from j to i; when i=j, no condition is imposed, thus there may be cycles of length 1: still all edges are one-way

• If relation R is symmetric, then whenever there is an edge from vertex i to j, then there is an edge from vertex j to i.

Page 5: Properties of Relations In many applications to computer science and applied mathematics, we deal with relations on a set A rather than relations from.

Transitive Relations• A relation R on a set A is transitive if whenever aRb

and bRc, then aRc.• A relation R on A is not transitive if there exists a, b,

and c in A so that aRb and bRc, but aRc.– If such a, b, and c do not exist, then R is transitive

• R is transitive if and only if its matrix MR =[mij] has the property if mij=1 and mjk=1, then mik=1.

• If MRMR has a 1 in any position, then MR must have a 1 in the same position, i.e. if MRMR = MR, then R is transitive

– The converse is not true, i.e. if MRMR MR, then R may be transitive or may not be transitive

Page 6: Properties of Relations In many applications to computer science and applied mathematics, we deal with relations on a set A rather than relations from.

Transitive Relations

Theorem 1. A relation R is transitive if and only if it satisfies the following property: if there is a path of length greater than 1 from vertex a to vertex b, there is a path of length 1 from a to b (that is, a is related to b). Algebraically stated, R is transitive if and only if RnR for all n1.

Theorem 2. Let R be a relation on a set A, then (a) Reflexive of R means that aR(a) for all a in A.(b) Symmetry of R means that aR(b) if and only if

bR(a).(c) Transitivity of R means that if bR(a) and cR(b), then

cR(a) .

Page 7: Properties of Relations In many applications to computer science and applied mathematics, we deal with relations on a set A rather than relations from.

• A relation R on a set A is called an equivalence relation if it is reflexive, symmetric and transitive.

Theorem 1. Let P be a partition of a set A. Recall that the sets in P are called the blocks of P. Define the relation R on A as follows:aRb if only if a and b are members of the same block. Then R is an equivalence relation on A.

• R will be called the equivalence relation determined by P – each element in a block is related to every element in

the same block and only to these elements.

Lemma 1. Let R be an equivalence relation on A, and let aA and bA, then aRb if and only if R(a)=R(b).

Equivalence Relations and Partitions

Page 8: Properties of Relations In many applications to computer science and applied mathematics, we deal with relations on a set A rather than relations from.

Equivalence Relations and Partitions Theorem 2. Let R be an equivalence relation on A,

and let P be the collection of all distinct relative sets R(a) for a in A. Then P is a partition of A and R is the equivalence relation determined by P.

• If R is an equivalence relation on A, then the sets R(a) are called equivalence classes of R.

• The partition P constructed in Theorem 2 consists of all equivalence classes of R, denoted by A/R

• P is the quotient set of A, that is constructed from and determines R.

Page 9: Properties of Relations In many applications to computer science and applied mathematics, we deal with relations on a set A rather than relations from.

Equivalence Relations and Partitions

A general procedure for determining partitions A/R for a set A which is finite or countable:

step1: choose any element a of A and compute the equivalence class R(a)

step2: if R(a)A, choose an element b, not included in R(a), and compute the equivalence class R(b)

step3: if A is not the union of previously computed equivalence classes, then choose an element x of A that is not in any of those equivalence classes and compute R(x)

step4: repeat step3 until all element of A are included in the computed equivalence classes. If A is countable, this process could continue indefinitely. In that case, continue until a pattern emerges that allows to describe or give a formula for all equivalence classes.