Sentence examples for the involved matrix from inspiring English sources
In this paper, new error bounds for the linear complementarity problem are obtained when the involved matrix is a weakly chained diagonally dominant B-matrix.
Particularly, when the involved matrix is a B-matrix as a special class of (B^{S} -matrices, the new B^{S} -matricese withethat provided by Li et al. inew13].
In this paper, by reformulating the complementarity problem (1) as an implicit fixed point equation based on splittings of the system matrix A, we establish an accelerated modulus-based matrix splitting iteration algorithm and show the convergence analysis when the involved matrix of the WNCP is a P-matrix.
In practice, it strongly depends on the involved matrix and on the way the score distribution is approximated by round matrices.
When the involved matrix A in (1.1) is (A = W + iT), the convergent rate of the aforementioned Picard-HSS and nonlinear HSS-like methods maybe reduce.
The activation energy Q depends on the bond strengths, size of diffusing atoms, the elasticity of the matrix and the effective number of the involved matrix atoms.
One can efficiently compute Σ t+1 by leveraging algebraic tricks prompted by the structural properties of the involved matrices (Toeplitz and upper triangular).
Considering the dimensions of the involved matrices, it becomes clear that a real-world implementation must exploit sparsity in order to be feasible.
In comparison with other bases (for example, polynomial bases), one of the advantages of this method is, although the involved matrices have a large dimension, they contain a large percentage of zero entries, which keeps computational effort within reasonable limits.
Our cost function to tackle problem (7) originates from the popular off-norm function that measures the squared Frobenius norm of the off-diagonal entries of the involved matrices.
where K is an irrelevant constant, the involved matrixes are defined as D a = D a ξ T D a μ T T (26) Ω ( m ) = Λ ( m ) 0 0 Λ ( m ) with Λ ( m ) = diag 1 2 D a ξ x ^ ( m ) 2 + D a μ x ^ ( m ) 2 + ε (27).
