Event-Triggered Synchronization for Delayed Quaternion-Valued Inertial Fuzzy Neural Networks via Nonreduced Order Approach

Zhang, Ziye; Wang, Shuzhan; Wang, Xianghua; Wang, Zhen; Lin, Chong

doi:10.1109/tfuzz.2023.3241151

Cited by 17 publications

(1 citation statement)

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“…At present, the method of non-reduction has been widely developed to study the synchronization of INNs [34][35][36][37][38][39]. In particular, an event triggering controller was designed to investigate the synchronization of QV-INNs, and several criteria were derived by making full use of the non-reduction method in [40]. In [41], a type of full quaternion-valued inertial neural network (QV-INN) with time-varying delays was considered, and based on the direct analysis method, the synchronization was studied via PD control and its adaptive scheme.…”

Section: Introductionmentioning

confidence: 99%

Synchronization Analysis for Quaternion-Valued Delayed Neural Networks with Impulse and Inertia via a Direct Technique

Yu,

Xiong,

2024

Mathematics

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The asymptotic synchronization of quaternion-valued delayed neural networks with impulses and inertia is studied in this article. Firstly, a convergence result on piecewise differentiable functions is developed, which is a generalization of the Barbalat lemma and provides a powerful tool for the convergence analysis of discontinuous systems. To achieve synchronization, a constant gain-based control scheme and an adaptive gain-based control strategy are directly proposed for response quaternion-valued models. In the convergence analysis, a direct analysis method is developed to discuss the synchronization without using the separation technique or reduced-order transformation. In particular, some Lyapunov functionals, composed of the state variables and their derivatives, are directly constructed and some synchronization criteria represented by matrix inequalities are obtained based on quaternion theory. Some numerical results are shown to further confirm the theoretical analysis.

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