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However, in many practical singular system models, the matrix (A_{22}) may be singular.
In a matrix form this reduces to: (14 where the model vector m is made of the Gauss coefficients of the models, the matrix G can be derived from the expressions of the model given in the previous section (Eqs. (1)–(12)) and d is the data vector.
In both of the models, the matrix is populated with a collection of soluble viral and host molecules.
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Yet in others, like direction learning and topic modeling, the matrix parameter instead pops up in the algorithms as the natural tool to represent uncertainty.
In this model, the matrix (softer) phase is split to two parts.
The same damage model was used to model the matrix material within the tows.
In the proposed model, the matrix ΔB becomes constant at zero.
LWMF utilizes the local property to model the matrix by dividing the original matrix into sub-matrices and relieves the sparsity problem.
In the pedigree model, the matrix A is a numerator relationship matrix (twice the matrix of kinship coefficients) computed from a pedigree.
For this model, the matrix is uniform and the weighing vector's magnitude is uniform in all directions and equal to 1.
Two primary methods – the spoke model and the matrix model are used to represent these complexes.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com