residual norm steepest descent based iterative algorithms for sylvester tensor equations

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.

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عنوان ژورنال:
journal of mathematical modeling

ناشر: university of guilan

ISSN 2345-394X

دوره 2

شماره 2 2015

میزبانی شده توسط پلتفرم ابری doprax.com

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