Exponential synchronization of neural networks with time-varying delays and stochastic impulses

Sun, Yifan; Li, Lulu; Liu, Xiaoyang

doi:10.1016/j.neunet.2020.09.014

Cited by 28 publications

(3 citation statements)

References 42 publications

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“…Currently, three prominent cases are being studied: random impulsive intensity, random impulsive density, and both being random. For the case of random impulsive intensity, the impulsive strengths are assumed to be certain independent and identically distributed random variables or discrete‐time stochastic processes, see, for example, Sun, 5 Jiao, 6 and Zhang 7 . However, in all these studies, the impulsive density using the (average) dwell‐time‐based method gives an upper and lower limit to the number of impulses, which is a more stringent constraint.…”

Section: Introductionmentioning

confidence: 99%

Stability and guaranteed cost control for linear impulsive systems with random impulses: Application to stochastic event‐triggered control

Luo,

Zhong,

Jiang

et al. 2023

Intl J Robust & Nonlinear

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SummaryThis paper proposes a systematic framework for stability and guaranteed cost control of linear impulsive systems subject to random time‐ and event‐triggering impulses. Moment stability criteria and design methods of time‐ and event‐triggered controllers with guaranteed quadratic performance for the impulsive system are established. It shows that the proposed event‐triggered controller in the sense that it guarantees at least the same quadratic performance function bound as the designed time‐triggered guaranteed cost controller, however, with a larger, or at most equal, average inter‐transmission time. Based on the proposed framework of random‐impulses systems, a stochastic dynamic event‐triggered control strategy is proposed to solve sampled‐data control systems in the presents of sporadic measurements or stochastic sampling. Numerical simulations illustrate the effectiveness of the proposed theoretical results.

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Section: Introductionmentioning

confidence: 99%

Stability and guaranteed cost control for linear impulsive systems with random impulses: Application to stochastic event‐triggered control

Luo,

Zhong,

Jiang

et al. 2023

Intl J Robust & Nonlinear

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“…However, impulsive disturbance is often stochastic, while an impulsive controller can also exhibit randomness because of some unstable factors. Hence, it seems more reasonable that the impulsive strengths are stochastic [33][34][35]. The above classification may no longer be applicable when impulsive strengths are not determined.…”

Section: Introductionmentioning

confidence: 99%

Synchronization of Coupled Memristor Neural Networks with Time Delay: Positive Effects of Stochastic Delayed Impulses

Sun

Wang

et al. 2021

Neural Process Lett

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This paper mainly investigates the positive effects of delay-dependent impulses on the synchronization of delayed memristor neural networks. Different from traditional impulsive control, the impulsive sequence in this paper is assumed to have the Markovian property, and is not always stabilizing. Based on a useful inequality, mean square synchronization criterion is derived under such a kind of impulsive effect. It can be seen that the stochastic impulses play an impulsive controller role, if they are stabilizing in an "average" sense. The validity of the theoretical results is illustrated by a numerical example.

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“…Systems with such kinds of environmental fluctuations can be described by stochastic differential equations, which play a significant role in the population dynamics as they can provide some additional degree of realism compared to their corresponding deterministic counterparts (Renshaw, 1991). Thus, stochastic population systems, as an important application in ecological and biological systems, have attracted increasing attention (Sun et al, 2020;Deng and Liu, 2020;Jiang et al, 2020;Yu et al, 2019;Gao and Wang, 2019;Liu et al, 2017;. Especially, stochastic plankton systems with white noise have been the common area of interest among researchers Chattopadhyay, 2003a, 2003b;Yu et al, 2019;Zhao et al, 2017;Liao et al, 2019;Xia et al, 2020;Zhao et al, 2020; in recent years and many interesting results have been shown.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear dynamics of plankton ecosystem with impulsive control and environmental fluctuations

Li¹

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It is well known that the density of plankton populations always increases and decreases or keeps invariant for a long time, and the variation of plankton density is an important factor influencing the real aquatic environments, why do these situations occur? It is an interesting topic which has become the common interest for many researchers. As the basis of the food webs in oceans, lakes, and reservoirs, plankton

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Exponential synchronization of neural networks with time-varying delays and stochastic impulses

Cited by 28 publications

References 42 publications

Stability and guaranteed cost control for linear impulsive systems with random impulses: Application to stochastic event‐triggered control

Stability and guaranteed cost control for linear impulsive systems with random impulses: Application to stochastic event‐triggered control

Synchronization of Coupled Memristor Neural Networks with Time Delay: Positive Effects of Stochastic Delayed Impulses

Nonlinear dynamics of plankton ecosystem with impulsive control and environmental fluctuations

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