An implicit iterative algorithm with a tuning parameter for Itô Lyapunov matrix equations
Ying Zhang,
Ai-Guo Wu and
Hui-Jie Sun
International Journal of Systems Science, 2018, vol. 49, issue 2, 425-434
Abstract:
In this paper, an implicit iterative algorithm is proposed for solving a class of Lyapunov matrix equations arising in Itô stochastic linear systems. A tuning parameter is introduced in this algorithm, and thus the convergence rate of the algorithm can be changed. Some conditions are presented such that the developed algorithm is convergent. In addition, an explicit expression is also derived for the optimal tuning parameter, which guarantees that the obtained algorithm achieves its fastest convergence rate. Finally, numerical examples are employed to illustrate the effectiveness of the given algorithm.
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:49:y:2018:i:2:p:425-434
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DOI: 10.1080/00207721.2017.1407009
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