 The accelerated gradient based iterative algorithm for solving a class of generalized Sylvester-transpose matrix equationYa-Jun Xie and Chang-Feng Ma Applied Mathematics and Computation, 2016, vol. 273, issue C, 1257-1269 Abstract: In this paper, we present an accelerated gradient based algorithm by minimizing certain criterion quadratic function for solving the generalized Sylvester-transpose matrix equation AXB+CXTD=F. The idea is from (Ding and Chen, 2005; Niu et al., 2011; Wang et al., 2012) in which some efficient algorithms were developed for solving the Sylvester matrix equation and the Lyapunov matrix equation. On the basis of the information generated in the previous half-step, we further introduce a relaxation factor to obtain the solution of the generalized Sylvester-transpose matrix equation. We show that the iterative solution converges to the exact solution for any initial value provided that some appropriate assumptions. Finally, some numerical examples are given to illustrate that the introduced iterative algorithm is efficient. Keywords: Generalized Sylvester-transpose matrix equation; Accelerated gradient based iterative (AGBI) algorithm; Relaxation factor; Numerical test (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:273:y:2016:i:c:p:1257-1269 DOI: 10.1016/j.amc.2015.07.022 Access Statistics for this article Applied Mathematics and Computation is currently edited by Theodore Simos More articles in Applied Mathematics and Computation from Elsevier |
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