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In this context, the use of so-called complementary matrices play an important role.
Structured matrices play an important role in the numerical solution of practical problems, because it is possible to develop fast algorithms for their triangular factorization.
The lower bounds for the rank of matrices play an important role in diagnosing nonsingular matrices.
In other words, the matrix A is Hermitian if and only if A = A ¯ T, where A ¯ T denotes the conjugate transpose of matrix A. Hermitian matrices play an important role in statistical mechanics [1], engineering; in cases such as communication, to describe n-dimensional signal cross-correlation properties, like conjugate symmetry, we can use Hermitian matrices.
As we know, the weighting matrices play an important role in parallel multisplitting iterative methods, but the weighting matrices in all the above-mentioned methods are determined in advance, they are not known to be good or bad, and this influences the efficiency of parallel methods.
In summary, FAP+ 3D matrices represent a permissive environment for pancreatic (and breast cancer) invasion, and perhaps these matrices play an equally important role along with the epithelial cell component.
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These regular matrices play a very important role in summing nonconvergent or convergent sequences and series.
Random measurement matrices play a critical role in successful recovery with the compressive sensing (CS) framework.
The eigenvalues of these r-mode sample covariance matrices play a major role in the model order estimation step.
It is clear that these matrices play a significant role in analyzing the structure's dynamic behavior due to structural damages.
Mechanical signals transferred between a cell and its extracellular matrix play an important role in regulating fundamental cell behavior.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com