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An accelerated Jacobi-gradient based iterative algorithm for solving sylvester matrix equations

An accelerated Jacobi-gradient based iterative algorithm for solving Sylvester matrix equations
Authors: Tian, Zhaolu; Tian, Maoyi; Gu, Chuanqing; Hao, Xiaoning;

An accelerated Jacobi-gradient based iterative algorithm for solving sylvester matrix equations

Abstract

In this paper, an accelerated Jacobi-gradient based iterative (AJGI) algorithm for solving Sylvester matrix equations is presented, which is based on the algorithms proposed by Ding and Chen [6], Niu et al. [18] and Xie et al. [25]. Theoretical analysis shows that the new algorithm will converge to the true solution for any initial value under certain assumptions. Finally, three numerical examples are given to verify the eficiency of the accelerated algorithm proposed in this paper.

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Keywords

convergence, Numerical methods for matrix equations, Matrix equations and identities, Sylvester matrix equations, Jacobi-gradient based algorithm, accelerated

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
34
Top 10%
Top 10%
Top 10%
gold