Sparse QR DecompositionQR decomposition of a large sparse matrix is used to solve the linear least squares (LS) problem arising in power system state estimation. It can also be used to estimate rank of matrix (rank revealindoi:10.1007/978-1-4615-0823-6_5S. A. Soman...
The Q-R decomposition is obtained for various purposes, one of which is obtaining a least squares solution of over-determined linear equations. If you have a class of matrices for which both are applicable, and the matrices are well-conditioned, I would expect Pardiso to be more efficient, ...
In this article, for solution of a system of linear algebraic equations Ax = b with a large sparse coefficient matrix A, the QR-decomposition with iterative refinement (QRIR) is compared with the QR-decomposition by means of Givens rotations(QRGR), which is without iterative refinement and ...
We present a parallel computational method for the QR decomposition with column pivoting of a sparse matrix by means of Modified Gram-Schmidt orthogonalization. Nonzero elements of the matrix M to beDOI: 10.1007/3-540-61142-8_609 被引量: 15 年份...
Python wrapper for SuiteSparseQR This module wraps theSuiteSparseQRdecomposition function for use withSciPy. This is Matlab's sparse[Q,R,E] = qr(). For some reason, no one ever wrapped that function of SuiteSparseQR for Python. Also wrapped are the SuiteSparseQR solvers forA x = bfor the...
I understand the technique by which the over-determined system is solved reasonably well using QR decomposition, but I wanted to check how Eigen solves the under-determined system. To solve the equationA.transpose() x = bEigen doesn't seem to be performing the minimum norm solution which wo...
In the recently presented sparse matrix extension of MATLAB, there is no routine for sparse QR factorization. Sparse linear least-squares problems are instead solved by the augmented system method. The accuracy in computed solutions is strongly dependent on a scaling parameter δ. Its optimal ...
mkl_sparse_qr.h Description Themkl_sparse_?_qrroutine computes the QR decomposition for the matrix of a sparse linear systemA*x=b, so thatA=Q*RwhereQis the orthogonal matrix andRis upper triangular, and calculates the solution. NOTE: ...
它们提供了guide explaining their sparse solver classes。由于问题集中在SparseQR上，文档指出初始化求解...
The result of X = A/B is the solution to A = XB, which is n .(B' A')' Full Matlab computes AnB by LU 16 factorization with partial pivoting if A is square, or by QR factorization with column pivoting if not. 3.4.1. The sparse linear equation solver. Like full Matlab, sparse ...