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Exact(13)
Let P be a square matrix.
Let Q be a square matrix.
Theorem 1 Let V be a square matrix such that V 2 = 2 x V − I.
The zero-forcing decoder is used because H s may not be a square matrix.
Let (mathcal{S}) be a square matrix of order (l geq1) which has complex entries.
In this case, the ({mathbf{G}}) matrix will be a square matrix which could be invertible if the determinant of the matrix is different from zero.
Similar(47)
Let, where is a square matrix.
Thus, the filter matrix is a square matrix, and the input/output signal vectors are column vectors.
Along the way, however, its fundamental rules (such as being a square matrix) have been challenged.
LU decomposition is a decomposition of the form A=LU where A is a square matrix.
The adjacency matrix A of a simple graph (material) with n vertices (atoms) is a square matrix (n × n) with entries aij=1 if atom i is connected to atom j, and aij=0 otherwise.
More suggestions(18)
be a fundamental matrix
be a square search-window
be a deterministic matrix
be a private matrix
be a square planar
be a regular matrix
be a useful matrix
be a square base
be a square antiprism
be a square wave
be a random matrix
be a orthogonal matrix
be a normal matrix
be a rectangular matrix
be a promising matrix
be a square meal
be a square block
be a square brick
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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