Pinning Impulsive Synchronization of Stochastic Memristor-based Neural Networks with Time-varying Delays

Fu, Qianhua; Cai, Jingye; Zhong, Shouming; Yu, Yongbin

doi:10.1007/s12555-018-0295-3

Cited by 21 publications

(7 citation statements)

References 36 publications

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“…Over the past few decades, the stability analysis of impulsive dynamical systems has been extensively investigated 23‐27 . In Reference 5, various stability criteria before 2014 were summarized for stochastic impulsive systems.…”

Section: Introductionmentioning

confidence: 99%

Stability criteria of random delay differential systems subject to random impulses

Zhang

Feng

et al. 2021

Intl J Robust & Nonlinear

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This article investigates the stability of random impulsive delay differential systems with the kind of random impulsive intensity determined by an arbitrary random sequence or an irreducible aperiodic Markov chain. Moreover, the continuous dynamics are described by random delay differential equations whose random disturbances are driven by second‐order moment processes. Based on the approaches of average impulsive interval and mode‐dependent average impulsive interval, the criteria of global asymptotic stability in probability and exponential stability in mth moment are constructed, respectively. In the end, the feasibility of the proposed theoretical results is verified by an example.

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Section: Introductionmentioning

confidence: 99%

Stability criteria of random delay differential systems subject to random impulses

Zhang

Feng

et al. 2021

Intl J Robust & Nonlinear

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“…And the produced time delays may cause the stability of the system and even results in oscillation, divergence, and instability phenomena 27‐30 . Thus, much achievement has been devoted to analyze dynamic behaviors of MNNs with various types of time delays (see, eg, References 6 and 31‐35). For instance, the discussed MNNs considered the discrete time‐varying delay in References 6,31,32, and 35.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, much achievement has been devoted to analyze dynamic behaviors of MNNs with various types of time delays (see, eg, References 6 and 31‐35). For instance, the discussed MNNs considered the discrete time‐varying delay in References 6,31,32, and 35. In Reference 31, the authors investigated the stability issue for uncertain MNNs with time‐varying delays.…”

Section: Introductionmentioning

confidence: 99%

“…In Reference 32, the robust stabilization problem of memristor‐based coupled NNs with time‐varying delays was studied. In Reference 35, by designing via pinning impulsive controller, the exponential and asymptotical synchronization issues of stochastic MNNs with time‐varying delays were addressed. From the above literature studies, 6,31,32 it is easy to see that the time delay is usually assumed to appear in simple or single form.…”

Section: Introductionmentioning

confidence: 99%

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New results on stability analysis and extended dissipative conditions for uncertain memristive neural networks with two additive time‐varying delay components and reaction‐diffusion terms

Cao

Xiong

et al. 2020

Intl J Robust & Nonlinear

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This article deals with the problems of exponential stability and extended dissipative analysis for a class of uncertain memristive neural networks (MNNs) with additive time-varying delays and reaction-diffusion terms. On the basis of generalized Lyapunov functional approach, Hardy-Poincarè inequality, Jensen's inequality, as well as some other inequality techniques, it is shown that the issues of exponential stability and extended dissipativity for the uncertain reaction-diffusion MNNs are solvable if a set of linear matrix inequalities (LMIs) proposed are feasible. As a special case, the conditions on exponential stability and extended dissipativity for the uncertain MNNs with additive time-varying delays are also obtained and given in terms of nonlinear matrix inequalities (NMIs). The obtained NMIs can be transformed as general LMIs via using a new quadratic convex combination skill. Moreover, the developed sufficient conditions for the uncertain delayed MNNs with and without reaction-diffusion terms can be easily checked by Matlab LMI control toolbox, and three numerical examples with simulation are provided to show the effectiveness and applicability of the theoretical results.

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“…In the literature on impulsive synchronization of chaotic systems with master and slave memristors, some important issues have been investigated, such as time-delayed in memristor-based chaotic systems [33], TS fuzzy model [34], pinning impulsive control [35], finite-time synchronization [36], etc. It should be noted that the impulsive control schemes proposed in the above literatures were carried out at fixed impulsive instants.…”

Section: Introductionmentioning

confidence: 99%

Variable Impulsive Synchronization of Memristor-Based Chaotic Systems With Actuator Saturation

Xiong

Zhang

2019

IEEE Access

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This paper is concerned with the synchronization of memristor-based chaotic system subject to actuator saturation via variable impulsive control. Firstly, a memristor-based circuit model is considered, and an impulsive controller subject to actuator saturation is designed. Based on the Lyapunov stability theory and some inequality techniques, some sufficient conditions are derived to guarantee the asymptotic synchronization of the memristor-based chaotic systems. Compared with the common fixed impulsive control, the variable impulsive control used in this paper is more reliable in practical application. Finally, the numerical simulations are given to verify the effectiveness of the proposed method.

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Pinning Impulsive Synchronization of Stochastic Memristor-based Neural Networks with Time-varying Delays

Cited by 21 publications

References 36 publications

Stability criteria of random delay differential systems subject to random impulses

Stability criteria of random delay differential systems subject to random impulses

New results on stability analysis and extended dissipative conditions for uncertain memristive neural networks with two additive time‐varying delay components and reaction‐diffusion terms

Variable Impulsive Synchronization of Memristor-Based Chaotic Systems With Actuator Saturation

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