square matrix


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square matrix

n. Mathematics
A matrix with equal numbers of rows and columns.

square matrix

n
(Mathematics) maths a matrix in which the number of rows is equal to the number of columns

square′ ma′trix


n.
a mathematical matrix in which the number of rows is equal to the number of columns.
[1930–35]
ThesaurusAntonymsRelated WordsSynonymsLegend:
Noun1.square matrix - a matrix with the same number of rows and columns
matrix - (mathematics) a rectangular array of quantities or expressions set out by rows and columns; treated as a single element and manipulated according to rules
diagonal - (mathematics) a set of entries in a square matrix running diagonally either from the upper left to lower right entry or running from the upper right to lower left entry
diagonal matrix - a square matrix with all elements not on the main diagonal equal to zero
determinant - a square matrix used to solve simultaneous equations
Latin square - a square matrix of n rows and columns; cells contain n different symbols so arranged that no symbol occurs more than once in any row or column
magic square - a square matrix of n rows and columns; the first n^2 integers are arranged in the cells of the matrix in such a way that the sum of any row or column or diagonal is the same
nonsingular matrix - a square matrix whose determinant is not zero
singular matrix - a square matrix whose determinant is zero
Translations
References in periodicals archive ?
Specially, Gentry, Sahai, and Waters (GSW) used the approximate eigenvector approach to propose a LWE-based FHE scheme in 2013 [10] whose ciphertext is a square matrix, and thus multiplication of ciphertexts is the multiplication of square matrixes that make homomorphic multiplication become very nature and simple.
Item score matrix could be expressed as [F.sub.ixj; a Matrix [M.sub.axi] whose mean value was 0 and variance was [[alpha].sup.2.sub.M] and a random number matrix [N.sub.axj] whose mean value and variance were 0 and [[alpha].sup.2.sub.N] respectively were produced by MATLAB [5], in which a refers to the dimension of decomposition, [M.sub.axi] refers to a dimensional characteristic square matrix of users, and [N.sub.axj] refers to the a-dimensional characteristic square matrix of item.
For a square matrix with degree k, matrix A [member of] [R.sup.nxn] denoted by A(k) and was defined by recursive operation on k = 2,3, ...:
where each diagonal block [A.sub.i] is a square matrix, for all 1 [less than or equal to] i [less than or equal to] n.
Li, "A family of iterative methods for computing the approximate inverse of a square matrix and inner inverse of a non-square matrix," Applied Mathematics and Computation, vol.
The problem of solving linear equations over the quaternion field H(R), has been studied in [3] and [8] making use of quaternionic determinant and inverse square matrix, subjects that will be used in this work.
It is not possible to write such a system in the matrix form, analogous to (2.12) with a square matrix.
For the statically determinate structures [10] and after inserting in the set of equations (8) the known values of reactions on the supports, matrix A is reduced to a square matrix [K.sub.e] of dimensions 2N x 2N, in two dimensions and 3N x 3N in three dimensions.
AB = ([c.sub.ij]) is a square matrix of n order, where [c.sub.ij] = [[summation].sup.m.sub.k=1] [a.sub.ik] [b.sub.kj] 1, 2, ..., n.
(ii) C is a square matrix, of size m, with elements of vector U on the main diagonal and zero elsewhere:
diag(x) denotes the square matrix. G = [[g.sub.1], [g.sub.2], ..., [g.sub.K]] is the gain vector.