a matrix lsqr algorithm for solving constrained linear operator equations
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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.
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Journal title:
bulletin of the iranian mathematical societyPublisher: iranian mathematical society (ims)
ISSN 1017-060X
volume 40
issue 1 2014
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