Using sparse matrices to store data that contains a large number of zero-valued elements can both save a significant amount of memory and speed up the processing of that data. sparse is an attribute that you can assign to any two-dimensional MATLAB matrix that is composed of double or logical elements.
The sparse attribute allows MATLAB to:
Store only the nonzero elements of the matrix, together with their indices.
Reduce computation time by eliminating operations on zero elements.
For full matrices, MATLAB stores every matrix element internally. Zero-valued elements require the same amount of storage space as any other matrix element. For sparse matrices, however, MATLAB stores only the nonzero elements and their indices. For large matrices with a high percentage of zero-valued elements, this scheme significantly reduces the amount of memory required for data storage.
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A sparse matrix is matrix that allows special techniques to take advantage of large number of zero element. Application of sparse matrix is classification and relationship analysis in large data base system - SPARCOM
The comparative form of sparse is sparser
Vector matrix has both size and direction. There are different types of matrix namely the scalar matrix, the symmetric matrix, the square matrix and the column matrix.
No. A matrix polynomial is an algebraic expression in which the variable is a matrix. A polynomial matrix is a matrix in which each element is a polynomial.
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