Fixed-time synchronization of coupled Cohen–Grossberg neural networks with and without parameter uncertainties

Huang, Yanli; Qiu, Shui-Han; Ren, Shun-Yan; Zheng, Zewei

doi:10.1016/j.neucom.2018.07.013

Cited by 42 publications

(15 citation statements)

References 49 publications

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“…Due to the effect of environmental noise and model error, it is usually impossible to obtain the accurate value of parameters in CNNs in many cases. Therefore, it is of great significance and interesting to research the dynamical behaviors of CNNs with parameter uncertainties [51][52][53][54]. The authors [51] concerned the problems of generalized synchronization and pinning control for delayed CNNs with and without parameter uncertainties.…”

Section: Introductionmentioning

confidence: 99%

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: Introductionmentioning

confidence: 99%

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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“…Because of this merit, FTS has attracted great attention in lots of fields, including power system [15], traffic [16], and consensus [17]. So far, some inter-esting results on FTS of NN have been presented [18][19][20][21][22][23][24]. Based on Lyapunov functionals, FTS for recurrent memristive NN (MNN) with time delay was presented in [21].…”

Section: Introductionmentioning

confidence: 99%

“…Remark 4 Recently, many excellent results on FTS of RVNN and CVNN[18][19][20][21][22][23][24] have been presented. Compared with previous works, QVNN possess superiority in dealing with multidimensional problems, and they have widely potential application in engineering field.…”

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confidence: 99%

Fixed time synchronization of delayed quaternion-valued memristor-based neural networks

et al. 2020

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This paper investigates the fixed time synchronization issue for a class of quaternion-valued memristor-based neural networks (QVMNN) at the presence of time varying delays. Differential inclusion and fixed time stability theory are used, and new synchronization conditions are formulated to achieve the synchronization of delayed QVMNN within a fixed time based on a Lyapunov function and a suitable controller. The feasibility of the proposed method is shown through numerical simulations.

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“…Recently, CNNs have been attracted wide attention because of their extensive applications in various prospects, such as brain science and secure communication. Consequently, a great quantity of meaningful research results on CNNs have been published [10,27,28,42,49]. In [10], the fixed-time synchronization for a kind of CNNs with parameter uncertainties was investigated.…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, a great quantity of meaningful research results on CNNs have been published [10,27,28,42,49]. In [10], the fixed-time synchronization for a kind of CNNs with parameter uncertainties was investigated. The authors discussed the synchronization of memristor-based recurrent CNNs with time-varying delays in [49].…”

Section: Introductionmentioning

confidence: 99%

General decay anti-synchronization of multi-weighted coupled neural networks with and without reaction–diffusion terms

Huang

Hou

Yang

2019

Neural Comput & Applic

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The network models of multi-weighted coupled neural networks (MWCNNs) and multi-weighted coupled reaction-diffusion neural networks (MWCRDN-Ns) with and without delayed coupling are presented in this paper, respectively. Firstly, on account of the definitions of ψ-type stability and ψ-type function, the concept of decay anti-synchronization is proposed. Then, we investigate the decay anti-synchronization of MWC-NNs with and without delayed coupling by designing appropriate nonlinear controllers, and several criteria for ensuring decay anti-synchronization are inferred by means of Lyapunov functional method as well as inequality techniques. Similarly, some conditions for decay anti-synchronization of MWCRDNNs with and without delayed coupling are also respectively derived. Lastly, two numerical examples with simulations are given to validate the correctness of these derived results.

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Fixed-time synchronization of coupled Cohen–Grossberg neural networks with and without parameter uncertainties

Cited by 42 publications

References 49 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

Fixed time synchronization of delayed quaternion-valued memristor-based neural networks

General decay anti-synchronization of multi-weighted coupled neural networks with and without reaction–diffusion terms

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