New fixed-time stability criterion and fixed-time synchronization of neural networks via non-chattering control

Tang, Qian; Qu, Shaocheng; Wang, Zheng; Du, Xingqiang; Tu, Zhengwen

doi:10.1007/s00521-022-07975-y

Cited by 9 publications

(2 citation statements)

References 40 publications

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“…FITS aims to attain consistency of states among all neurons in a network within a finite time, regardless of initial conditions. There are several outstanding results about FITS [21][22][23][24]. Tang et al designed a continuous sampling and non-chattering controller to achieve the FITS of neural networks [21].…”

Section: Introductionmentioning

confidence: 99%

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Fixed/Preassigned-Time Synchronization of Fuzzy Memristive Fully Quaternion-Valued Neural Networks Based on Event-Triggered Control

Jia,

Hu,

Jiang

2024

Mathematics

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In this paper, the fixed-time and preassigned-time synchronization issues of fully quaternion-valued fuzzy memristive neural networks are studied based on the dynamic event-triggered control mechanism. Initially, the fuzzy rules are defined within the quaternion domain and the relevant properties are established through rigorous analysis. Subsequently, to conserve resources and enhance the efficiency of the controller, a kind of dynamic event-triggered control mechanism is introduced for the fuzzy memristive neural networks. Based on the non-separation analysis, fixed-time and preassigned-time synchronization criteria are presented and the Zeno phenomenon under the event-triggered mechanism is excluded successfully. Finally, the effectiveness of the theoretical results is verified through numerical simulations.

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Section: Introductionmentioning

confidence: 99%

“…There are several outstanding results about FITS [21][22][23][24]. Tang et al designed a continuous sampling and non-chattering controller to achieve the FITS of neural networks [21]. The FITS of memristor-based neural networks was investigated by a continuous sampling feedback control in [24].…”

Section: Introductionmentioning

confidence: 99%