Department of Mathematics Faculty of Mathematical Sciences Shahid Beheshti University, G.C., Evin, Tehran 19839 Iran
Abstract
In this work, an iterative method based on a matrix form of LSQR algorithm is constructed for solving the linear operator equation $mathcal{A}(X)=B$ and the minimum Frobenius norm residual problem $||mathcal{A}(X)-B||_F$ where $Xin mathcal{S}:={Xin textsf{R}^{ntimes n}~|~X=mathcal{G}(X)}$, $mathcal{F}$ is the linear operator from $textsf{R}^{ntimes n}$ onto $textsf{R}^{rtimes s}$, $mathcal{G}$ is a linear self-conjugate involution operator and $Bin textsf{R}^{rtimes s}$. Numerical examples are given to verify the efficiency of the constructed method.
Hajarian, M. (2014). A matrix LSQR algorithm for solving constrained linear operator equations. Bulletin of the Iranian Mathematical Society, 40(1), 41-53.
MLA
Hajarian, M. "A matrix LSQR algorithm for solving constrained linear operator equations", Bulletin of the Iranian Mathematical Society, 40, 1, 2014, 41-53.
HARVARD
Hajarian M. (2014). 'A matrix LSQR algorithm for solving constrained linear operator equations', Bulletin of the Iranian Mathematical Society, 40(1), pp. 41-53.
CHICAGO
M. Hajarian, "A matrix LSQR algorithm for solving constrained linear operator equations," Bulletin of the Iranian Mathematical Society, 40 1 (2014): 41-53,
VANCOUVER
Hajarian M. A matrix LSQR algorithm for solving constrained linear operator equations. BIMS. 2014;40(1):41-53.
