Impulsive control for passivity and exponential synchronization of coupled neural networks with multiple weights

Tang, Hong-An; Wang, Jinliang; Wang, Lidan; Hu, Xiaofang; Zhou, Yue; Duan, Shukai

doi:10.1016/j.jfranklin.2019.05.010

Cited by 32 publications

(11 citation statements)

References 43 publications

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“…Therefore, it is more reasonable to describe some real-world networks by utilizing the MWCNNs. However, there are only a few results reported on the passivity and synchronization of MWCNNs [48,49], and it is worth devoting more efforts on this topic. As far as we know, the event-triggered passivity and synchronization for MWCNNs have not been considered before, which motivates our research work in this paper.…”

Section: Remarkmentioning

confidence: 99%

“…Moreover, multi-weighted CNNs (MWCNNs) have become a very hot topic due to their broad application foreground. Some standards were established to ensure passivity and synchronization for MWCNNs [48][49][50]. Tang et al [49] investigated the passivity and exponential synchronization for two classes of MWCNNs with and without time delays.…”

Section: Introductionmentioning

confidence: 99%

“…Some standards were established to ensure passivity and synchronization for MWCNNs [48][49][50]. Tang et al [49] investigated the passivity and exponential synchronization for two classes of MWCNNs with and without time delays. It is regrettable that the passivity and synchronization for MWCNNs with event-triggered communication have rarely been considered.…”

Section: Introductionmentioning

confidence: 99%

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Event‐triggered communication for passivity and synchronisation of multi‐weighted coupled neural networks with and without parameter uncertainties

Wang

Huang

Yang

2020

IET Control Theory & Applications

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A multi-weighted coupled neural networks (MWCNNs) model with event-triggered communication is studied in this paper. On the one hand, the passivity of the presented network model is studied by utilizing Lyapunov stability theory and some inequality techniques, and a synchronization criterion based on the obtained output-strict passivity condition of MWCNNs with event-triggered communication is derived. On the other hand, some robust passivity and robust synchronization criteria based on output-strict passivity of the proposed network with uncertain parameters are presented. At last, two numerical examples are provided to testify the effectiveness of the output-strict passivity and robust synchronization results.

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Section: Remarkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Event‐triggered communication for passivity and synchronisation of multi‐weighted coupled neural networks with and without parameter uncertainties

Wang

Huang

Yang

2020

IET Control Theory & Applications

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“…Remark 5: Compared with [40], the main difficulties in studying the FTP and FTS of MDCNNs with impulsive control come from the design of the impulsive controller and the proofs of these theorems. By designing the impulsive controller and the Lyapunov functional and using inequality techniques, this paper considers the FTP and FTS of MDCNNs (see Theorems 1-3).…”

Section: Impulsive Control For Ftsmentioning

confidence: 99%

“…Moreover, CNNs can reach synchronization and passivity only by using small impulsive control gains. However, the problems of synchronization and passivity for multiple weighted CNNs have rarely been discussed with the aid of impulsive control schemes [40]. Tang et al [40] devised impulsive controllers to ensure that the multiple weighted CNNs reached passivity and synchronization.…”

Section: Introductionmentioning

confidence: 99%

Finite-Time Synchronization and Passivity of Multiple Delayed Coupled Neural Networks via Impulsive Control

2020

Self Cite

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This paper focuses on the finite-time passivity (FTP) and finite-time synchronization (FTS) for multiple delayed coupled neural networks (MDCNNs) with and without uncertain parameters. A novel FTP criterion for MDCNNs with different dimensions of input and output is derived by designing an impulsive controller and using the Jensen's inequality. Then, by means of the Lyapunov functional and integral inequality techniques, a sufficient condition is established to ensure the FTS of MDCNNs via impulsive control. Furthermore, the robust FTP and FTS in MDCNNs are considered. Finally, a numerical example is given to demonstrate the validity of the presented results. INDEX TERMS Impulsive control, finite-time passivity, finite-time synchronization, multiple time delays, coupled neural networks.

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Passivity of Coupled Fractional-Order Neural Networks with Multiple State and Derivative Couplings

Wang

2024

Dynamical Behaviors of Fractional-Order Complex Dynamical Networks

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Impulsive control for passivity and exponential synchronization of coupled neural networks with multiple weights

Cited by 32 publications

References 43 publications

Event‐triggered communication for passivity and synchronisation of multi‐weighted coupled neural networks with and without parameter uncertainties

Event‐triggered communication for passivity and synchronisation of multi‐weighted coupled neural networks with and without parameter uncertainties

Finite-Time Synchronization and Passivity of Multiple Delayed Coupled Neural Networks via Impulsive Control

Passivity of Coupled Fractional-Order Neural Networks with Multiple State and Derivative Couplings

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