Fixed-time projective synchronization of delayed memristive neural networks via aperiodically semi-intermittent switching control

Pu, Hao; Li, Fengjun

doi:10.1016/j.isatra.2022.07.022

Cited by 19 publications

(3 citation statements)

References 46 publications

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“…Remark 1 Markov switching is applied in the switching topology, which is different from [36][37][38][39]. Based on the negative effect of communication time delay on the network to finally reach synchronization, [36][37][38] used a pinning interval controller, a periodic semi-intermittent controller, and an adaptive aperiodically intermittent controller to control systems, respectively.…”

Section: 𝑟(𝑡) 𝑖𝑗mentioning

confidence: 99%

“…However, the aforementioned papers do not consider the effect on network synchronization when switching topology and time delay act on the network at the same time. Unlike above, in the case of switching topology, the effections of communication delay over networks are considered by [39], but where the switching process of topology is not a Markov process. Therefore, in our paper, an aperiodic intermittent controller is used to exert an effect on the network in the case where the Markovian switching topology has an effect on the network.…”

Section: 𝑟(𝑡) 𝑖𝑗mentioning

confidence: 99%

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Fixed-Time Synchronization of Markovian Switching Stochastic Complex Networks via Quantized Aperiodically Intermittent Control

Wu,

Yu,

et al. 2023

Preprint

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Fixed-time synchronization of Markovian switching stochastic complex networks via quantized aperiodically intermittent control is studied by this article. To achieve synchronization, a new control law is proposed. This control law greatly decreases the control expenses by saving communicating access and communicating bandwidth. By structuring Lyapunov functionals, and applying a designed comparison system, some simultaneity results are presented in terms of using the characteristics of Wiener processes. Comparatively speaking, there are two main features of this article. 1) Markov processes are applied to switching stochastic topological systems. 2) Fixed-time synchronization is achieved by a quantized intermittent controller to save resources. Finally, the result of the numerical simulation verifies the validity of the theoretical analysis.

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Section: 𝑟(𝑡) 𝑖𝑗mentioning

confidence: 99%

Section: 𝑟(𝑡) 𝑖𝑗mentioning

confidence: 99%

Fixed-Time Synchronization of Markovian Switching Stochastic Complex Networks via Quantized Aperiodically Intermittent Control

Wu,

Yu,

et al. 2023

Preprint

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“…Thus, in theory and application, studying FPS and AS are very important. Moreover, many results on FPS, PS and AS can be formed in literature for the integer-order NN systems [28][29][30][31]. The Mittag-Leffler function is a generalization of the exponential function for fractional-order calculus.…”

Section: Introductionmentioning

confidence: 99%

Function projective Mittag-Leffler synchronization of non-identical fractional-order neural networks

Baluni,

Yadav,

Das

et al. 2024

Phys. Scr.

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This article investigates the function projective Mittag-Leffler synchronization (FPMLS) between non-identical fractional-order neural networks (FONNs).The stability analysis is carried out using an existing lemma for the Lyapunov function in the FONN systems. Based on the stability theorem of FONN, a non-linear controller is designed to achieve FPMLS. Moreover, global Mittag-Leffler synchronization (GMLS) is investigated in the context of other synchronization techniques, such as projective synchronization (PS), anti-synchronization (AS) and complete synchonization (CS). Using the definition of the Caputo derivative, the Mittag-Leffler function and the Lyapunov stability theory, some stability results for the FPMLS scheme for FONN are discussed. Finally, the proposed technique is applied to a numerical example to validate its efficiency and the unwavering quality of the several applied synchronization conditions.

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Fixed‐Time Bipartite Synchronization of Stochastic Multiplex Signed Networks Via Quantized Generalized Intermittent Control

Qin,

Jiang,

Qiu

et al. 2024

Math Methods in App Sciences

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This study is dedicated to the fixed‐time (FDT) bipartite synchronization of stochastic multiplex signed networks via quantized generalized intermittent control (QGIC). Firstly, a multiplex network including signed graphs and stochastic disturbances is introduced. Secondly, a new lemma of FDT stability is established by using reduction to absurdity and mathematical induction. Thirdly, based on the proposed FDT stability and the stochastic analysis techniques, several sufficient conditions on FDT bipartite synchronization are derived by designing a novel QGIC strategy. Significantly, the designed controller is a unified form of periodic and aperiodic cases and is only activated in the work interval. At last, two numerical simulations are offered to validate the superiority and effectiveness of the theoretical findings.

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Fixed-time projective synchronization of delayed memristive neural networks via aperiodically semi-intermittent switching control

Cited by 19 publications

References 46 publications

Fixed-Time Synchronization of Markovian Switching Stochastic Complex Networks via Quantized Aperiodically Intermittent Control

Fixed-Time Synchronization of Markovian Switching Stochastic Complex Networks via Quantized Aperiodically Intermittent Control

Function projective Mittag-Leffler synchronization of non-identical fractional-order neural networks

Fixed‐Time Bipartite Synchronization of Stochastic Multiplex Signed Networks Via Quantized Generalized Intermittent Control

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