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The distances between the cities (nodes) are represented by a square matrix of floating point numbers.
Those types of systems can be viewed as an interconnection of single-input single-output isolated subsystems with the interconnection structure specified by a square matrix.
This gives rise to a graphical representation named Recurrence Plot (RP) constituted by a square matrix having as rows and columns the residues ordered along the sequence and where each recurrence (contact) is marked by a dot in the RP.
The features of any Markov chain can be also presented by a square matrix where the row and column labels represent the individual Markov states.
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As shown in Fig. 1 an undirected graph network that's weighted to clarify the procedure from this sample graph we are able to create the adjacency matrix and a distance matrix as well by creating a square matrix of size N × N (d i j ).
One first disease is taken, which is coded by the column vector di, and the outer product of this vector is made by itself (a square matrix is constructed that contains this autoassociation).
It is called identity matrix because multiplication with it leaves a matrix unchanged: AIn = ImA = A for any m-by-n matrix A. A square matrix A that is equal to its transpose, i.e., A = AT, is a symmetric matrix.
An n-by-n matrix is known as a square matrix of order n.
Also, ̂ will denote diagonalization, whether by suppression of the off-diagonal elements of a square matrix or by placement of the elements of a vector.
It is known by us that the rank of a square matrix is the number of its nonzero eigenvalues.
where M is a square matrix defined by m i k = d o i λ sin ( θ 0 i ) - d 0 k λ sin ( θ 0 k ).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com