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[ə′jās·ən·sē ‚mā·triks]
(mathematics)
For a graph with n Vertices, the n × n matrix A = aij, where the nondiagonal entry aij is the number of edges joining vertex i and Vertex j, and the diagonal entry aii is twice the number of loops at vertex i.
For a diagraph with no loops and not more than one are joining any two Vertices, an n × n matrix A = [aij ], in which aij = 1 if there is an are directed from vertex i to vertex j, and otherwise aij = 0.
References in periodicals archive ?
The Adjacency matrix [A.sup.(k)] of the workflow graph is drawn.
Then each thread examines the cycle existence of combination row vertices to see if they form a cycle or not regardless of the vertices order in the set by using a technique called "virtual adjacency matrix" test.
A = ([a.sub.ij]) [member of] [R.sup.nxn] is called the weighted adjacency matrix of G with nonnegative elements and [a.sub.ij] > 0 if and only if j [member of] [N.sub.i].
They exploit the duality between the canonical representation of graphs as abstract collections of vertices with edges and a sparse adjacency matrix representation.
In this paper, we consider the adjacency matrix for RC-graphs and the eigen values are taken into account and a handful of results are obtained.
One such matrix that is particularly useful is a vertex adjacency matrix A: matrix element [A.sub.jk] therein has the value unity if between vertices j and k there exist a single edge, or nought otherwise; this matrix of the same order as G is symmetric, with nil elements along the principal diagonal.
The matrix based on the prey-predator link, a binary relation, is, in fact, the adjacency matrix (defined below) of the digraph associated with a food web.