Module 17

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A matrix calculus for the analysis and generation of binary relations

Generalisations and applications
Part 1


A binary relation on a set
(1)
describes the ,,correspondence`` of two elements of , denoted
(2)
These ordered pairs from form a set
(3)

Examples of binary relations include: they find a wide range of applications in computer science.

Besides

and a binary relation on may also be represented and

In the entire application domain of computer science, electrical engineering,... , the specific classes of binary relations listed in table 1 are of high importance. Closely related to these classes is the question, how such binary relations can be identified, generated, extracted,... by algorithms in an efficient manner (notably for large ). The characteristic function and the relation matrix provide a good basis for these tasks. Therefore, in table 1, all definitions are given in - and -notation.

A binary relation is said to be ..., if the following conditions hold:
-notation -Notation
reflexive
irreflexive
symmetrical
antisymmetrical
asymmetrical
Clearly, , i.e., an asymmetrical binary relation is always irreflexive.
transitive
This equation has the form expression=constant. It can be transformed into variable=expression:

Thus, we arrive at the explicit definition

intransitive

where (inhibition).
Clearly, , i.e., an intransitive binary relation is always irreflexive.
equivalence relation reflexivity
symmetry
transitivity
irreflexive
partial ordering
asymmetry
transitivity
reflexive
partial ordering
reflexivity
antisymmetry
transitivity

table 1: classes of binary relations on

The marked definitions from table 1 which are given in -notation shall now be applied to the relation matrix of eq. (4).
For this, we first introduce two matrix operations describing the reflexive and symmetry of a binary relation , respectively:

Thus, we arrive at the definitions summarized in table 2 in -notation.
A binary relation is said to be ..., if it satisfies the following conditions:
(-notation)
reflexive   (identity matrix)
irreflexive   (zero matrix)
symmetrical
antisymmetrical
asymmetrical
table 2: classes of binary relations on , -notation
For the application of the transitivity and intransitivity condition
(7)

- in index notation -
(8)
to the relation matrix (fig. 1), eq. (8) has to be rearranged once more:
(9)


fig. 1: Application of eq. (7) to (cartesian notation)

According to eq. (9), the condition
(10)
rewritten
(11)
has to be checked for all entries of the relation matrix . The right hand side of equation (11) can be computed for all entries of the work space (compare fig. 2) by the algorithm (A1) given below:

In case of transitivity, the algorithm given above does not alter the work space. Similarly, in case of intransitivity, no change occurs in the work space if the algorithm described below is applied; here schlkA1 represents the original condition. Otherwise (in case the matrix is not intransitive), schlkA1 effects an alteration of the work space and hence constitutes an assignment operation (extending eq. (11), schlkA1 is defined as an assignment!).
We call the matrix operations just defined .


Algorithm (A1): Computation of it und it


fig. 2: Algorithm (A1), work space

Now, the other definitions from table 1 can be given in succinct -notation: table 3.
A binary relation is said to be ..., if it satisifies the condition
-notation
transitive it
intransitive it
equivalence relation
 
  it
irreflexive
partial ordering it
reflexive
partial ordering it
table 3: classes of binary relations in , -notation
Now, with the matrix calcuclus just derived, we are in the position to formulate the main Theorem about transitive relations in a constructive manner:


of a reflexive / irreflexive symmetrical / antisymmetrical relation on , exactly one reflexive /irreflexive symmetrical/antisymmetrical binary relation on can be obtained, which constitutes a "backbone" of . By we again obtain (fig. 3); thus reconstruction is the reversal of reduction.


fig. 3: main theorem about transitive relations


fig. 4: example to the main theorem about transitive relations


transitive closure

17.1

Prove that the matrix operations and satisfy the following conditions:

17.2

Prove that can be represented as a power series on the algebraic structure :
(16)
mit
(17)
(18)
(19)

17.3

Give a similar power series representing .

17.4

Prove that the solution of the matrix equations
(20)
on has the form
(21)

17.5

The relation graph of an asymmetrical binary relation on is cycle-free if and only if
(22)
Verify eq. (22) and prove that there is a smallest natural number with such that
(23)

17.6

Prove that if re there is a smallest natural number with such that
(24)
Then we have
(25)

17.7

Show that the up-iteration of a adjacency matrix yields the matrix of the transitive closure of the underlying graph.

17.8

Give a nontrivial asymmetrical binary relation on which is both transitive and intransitive.

17.9

Give a construction for


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