Sentence examples for matrix of g from inspiring English sources

We know that the matrix of g in the basis (mathsf {B}_infty ) is the infinite Jordan cell.

Throughout the paper, (bigtriangledown g(x)) will denote the (m times n) Jacobian matrix of g at x.

Formally, let A be a matrix of G × P data points, where G is the number of time periods evaluated (e.g., a week or a day) and P is the number of records per the above time period (e.g., samples per week or day).

For a graph G with n ( n ≥ 2 ) vertices, the adjacency matrix of G is, as usual, defined as the n × n matrix A ( G ) = [ a i j ] in which a i j = 1 if the i th and the j th vertices are adjacent, and a i j = 0 otherwise.

A G = (a ij ) n × n is the adjacency matrix of G, where a ij = 1 if (i, j) ∈ E is an edge of G, and a ij = 0 if (i, j) ∉ E. Genes and relationship between genes are represented by vertex and edge, respectively.

Assume furthermore that the intersection matrix of G = Gamma v0) - v(0) is negative definite.

More formally, given a fixed positive integer r, we define Fr as the family of graphs where for each G∈Fr, the rank of the adjacency matrix of G is at most r.

The Laplacian matrix of ((G, A)) is denoted by L.

Let ({mathbf{A}}(G)) be the adjacency matrix of G.

Let (B(G)) be the (vertex-edge) incidence matrix of G. Motivated by Nikiforov's idea and LEL, Jooyandeh et al. [9] introduced the concept of incidence energy of a graph G: if the singular values of (B(G)) are (sigma_{1},ldots_{2},sigma_{n}ma_{n}) then the incidence energy of G is (mathit{IE}(G =sum_{i=1}^{n}sigma_{i}=E(B(G))).

The matrix (Q(G =D(G)+ A(G)) is called the signless Laplacian matrix (or Q-matrix) of G. Since (Q(G)) is symmetric and positive semidefinite, it follows that its eigenvalues are real and nonnegative.