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Residual norm steepest descent based iterative algorithms for Sylvester tensor equations | ||
| Journal of Mathematical Modeling | ||
| مقاله 1، دوره 2، شماره 2، خرداد 2015، صفحه 115-131 اصل مقاله (313.54 K) | ||
| نوع مقاله: Research Article | ||
| نویسندگان | ||
| Fatemeh Panjeh Ali Beik* ؛ Salman Ahmadi-Asl | ||
| چکیده | ||
| Consider the following consistent Sylvester tensor equation \[\mathscr{X}\times_1 A +\mathscr{X}\times_2 B+\mathscr{X}\times_3 C=\mathscr{D},\] where the matrices $A,B, C$ and the tensor $\mathscr{D}$ are given and $\mathscr{X}$ is the unknown tensor. The current paper concerns with examining a simple and neat framework for accelerating the speed of convergence of the gradient-based iterative algorithm and its modified version for solving the mentioned Sylvester tensor equation without setting the restriction of the existence of a unique solution. Numerical experiments are reported which confirm the validity of the presented results. | ||
| کلیدواژهها | ||
| Sylvester tensor equation؛ iterative algorithm؛ Convergence | ||
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آمار تعداد مشاهده مقاله: 3,724 تعداد دریافت فایل اصل مقاله: 3,166 |
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