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See:
Description
Class Summary | |
CholeskyDecomposition | CholeskyDecomposition It is a special case of LU decomposition applicable only if matrix to be decomposed is symmetric positive definite. |
EigenvalueDecomposition | EigenvalueDecomposition If A is symmetric, then A = V*D*V' where the eigenvalue matrix D is diagonal and the eigenvector matrix V is orthogonal. |
LUDecomposition | LUDecomposition For an m-by-n matrix A with m >= n, the LU decomposition is an m-by-n unit lower triangular matrix L, an n-by-n upper triangular matrix U, and a permutation vector piv of length m so that A(piv,:) = L*U. |
MatrixPartition | MatrixPartition
Author: purangp Date: 12.03.2004 Time: 14:08:50 |
QRDecomposition | QRDecomposition For an m-by-n matrix A with m >= n, the QR decomposition is an m-by-n orthogonal matrix Q and an n-by-n upper triangular matrix R so that A = Q*R. |
SingularValueDecomposition | SingularValueDecomposition For an m-by-n matrix A with m >= n, the singular value decomposition is an m-by-n orthogonal matrix U, an n-by-n diagonal matrix S, and an n-by-n orthogonal matrix V so that A = U*S*V'. |
Util | Util
Author: purangp Date: 13.03.2004 Time: 13:54:46 |
Given a matrix of dimension mxn M -yields-> L,U,S and so on, where L,U,S are matrices and/or scalars
All operations on a matrix fitting this pattern can be found in this package.
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