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
Hajarian, M., "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.
