In numerical analysis and scientific computing, a sparse matrix or sparse array is a matrix in which most of the elements are zero. There is no strict...

In mathematics, particularly matrix theory, a band matrix or banded matrix is a sparse matrix whose non-zero entries are confined to a diagonal band, comprising...

directional gradient of a rasterized matrix. Once a matrix or a high-dimensional vector is transferred to a sparse space, different recovery algorithms...

Sparse matrix–vector multiplication (SpMV) of the form y = Ax is a widely used computational kernel existing in many scientific applications. The input...

adjacency matrix and the time needed to perform operations on them is dependent on the matrix representation chosen for the underlying matrix. Sparse matrix representations...

LAPACK defines various matrix representations in memory. There is also Sparse matrix representation and Morton-order matrix representation. According...

The Sparse Matrix Converter is an AC/AC converter which offers a reduced number of components, a low-complexity modulation scheme, and low realization...

to the star height of a regular language. It has also found use in sparse matrix computations (see Bodlaender et al. 1995) and logic (Rossman 2008)....

In linear algebra, a diagonal matrix is a matrix in which the entries outside the main diagonal are all zero; the term usually refers to square matrices...

hierarchical matrices (H-matrices) are used as data-sparse approximations of non-sparse matrices. While a sparse matrix of dimension n {\displaystyle n} can be represented...

statistics, the projection matrix ( P ) {\displaystyle (\mathbf {P} )} , sometimes also called the influence matrix or hat matrix ( H ) {\displaystyle (\mathbf...

to BLAS for handling sparse matrices have been suggested over the course of the library's history; a small set of sparse matrix kernel routines was finally...

following equivalent definition is in matrix form. Let V {\displaystyle V} be a p×p symmetric matrix, one can rewrite the sparse PCA problem as max T r ( Σ V )...

Charles E. (2009), "Parallel sparse matrix-vector and matrix-transpose-vector multiplication using compressed sparse blocks", ACM Symp. on Parallelism...

analysis, the entries of a matrix which change from zero to a non-zero value in the execution of an algorithm; see Sparse matrix § Reducing fill-in An issue...

factorization factors a matrix as the product of a lower triangular matrix and an upper triangular matrix (see matrix multiplication and matrix decomposition)...

Matrix multiplication algorithm, for practical implementation details Sparse matrix–vector multiplication Volker Strassen (Aug 1969). "Gaussian elimination...

sign matrix, a matrix of 0, 1, and −1 coefficients with the nonzeros in each row or column alternating between 1 and −1 and summing to 1 Sparse matrix, is...

be sparse, that is, contain few nonzero entries. Therefore, specifically tailored matrix algorithms can be used in network theory. The Hessian matrix of...

Hierarchical matrix, a data-sparse approximation of a non-sparse matrix Hilbert matrix, a square matrix with entries being the unit fractions Hollow matrix, a square...

matrices used in mathematics, science and engineering. A matrix (plural matrices, or less commonly matrixes) is a rectangular array of numbers called entries...

the matrix AP to A do j = 1, n forall(i=max(1,j-kl):min(m,j+ku)) A(i,j) = AP(i-j,j) end do print *,AP(0,:) ! the diagonal Sparse matrix Skyline matrix band...

designed to store sparse matrices, first described in 1982 as the format for the Harwell-Boeing collection of sparse matrix test problems. Matrix Market exchange...

document. For this reason, document-term matrices are usually stored in a sparse matrix format. As a result of the power-law distribution of tokens in nearly...

algorithm is the multiplication of matrix A {\displaystyle A} by a vector, so it is effective for a very large sparse matrix with appropriate implementation...

bandwidth of a symmetric sparse matrix Minimum degree algorithm: permute the rows and columns of a symmetric sparse matrix before applying the Cholesky...

indirect energy conversion by employing the Indirect Matrix Converter (Fig. 5) or the Sparse matrix converter which was invented by Prof. Johann W. Kolar...

James McKee, is an algorithm to permute a sparse matrix that has a symmetric sparsity pattern into a band matrix form with a small bandwidth. The reverse...

incomplete Cholesky factorization of a symmetric positive definite matrix is a sparse approximation of the Cholesky factorization. An incomplete Cholesky...

three fields: portfolio theory; sparse matrix methods; and simulation language programming (SIMSCRIPT). Sparse matrix methods are now widely used to solve...