Suppression of explosion by polynomial noise for nonlinear differential systems

Feng, Lichao; Li, Shoumei; Song, Renming; Li, Yemo

doi:10.1007/s11432-017-9340-4

Cited by 8 publications

(2 citation statements)

References 17 publications

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“…For an unstable system, various strategies have been introduced to stabilize it, such as sample control, impulse control, pinning control, feedback control, and intermittent control. Generally speaking, for stochastic differential systems, the feedback control can be divided into one in the drift part and one in the diffusion part, e.g., [12][13][14][15][16]. Here, the feedback control in the drift part is particularly noted for this paper.…”

Section: Introductionmentioning

confidence: 99%

Stabilization of Periodical Discrete Feedback Control for Markov Jumping Stochastic Systems

Liu

Feng

et al. 2021

Symmetry

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Motivated by the two strategies of intermittent control and discrete feedback control, this paper aims to introduce a periodically intermittent discrete feedback control in the drift part to stabilize an unstable Markov jumping stochastic differential system. It is illustrated that, by the approach of comparison principle, this can be achieved in the sense of almost sure exponential stability. Further, the stabilization theory is applied to Markov jumping stochastic recurrent neural networks.

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Section: Introductionmentioning

confidence: 99%

Stabilization of Periodical Discrete Feedback Control for Markov Jumping Stochastic Systems

Liu

Feng

et al. 2021

Symmetry

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“…Dear editor, Adaptive filtering algorithms have been widely applied in system identification, channel equalization, and echo cancellation over the past decades [1][2][3]. Generally, adaptive filtering algorithms can be generalized by the least mean square (LMS)-based algorithms.…”

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confidence: 99%