Bipartite synchronization of coupled delayed neural networks with cooperative-competitive interaction via event-triggered control

Sha Zhu, Haibo Bao and Jinde Cao

Physica A: Statistical Mechanics and its Applications, 2022, vol. 600, issue C

Abstract: In this paper, the issue of bipartite synchronization for coupled delayed neural networks (CDNNs) with cooperative-competitive interaction is firstly investigated via event-triggered control (ETC) mechanism, which greatly reduces communication bandwidth and computational burden. Firstly, in virtue of the signed graph theory, the model of CDNNs with cooperative-competitive interaction is established. Next, under the designed event-triggered controller, statical event-triggered control (SETC) condition and dynamical event-triggered control (DETC) condition for realizing bipartite synchronization of CDNNs are derived separately by utilizing Lyapunov functional method. Furthermore, an algebraic formula is provided to calculate the positive lower bound of the trigger interval, which indicates that Zeno-behavior does not arise. At last, the feasibility of the proffered ETC to realize bipartite synchronization is further demonstrated by an illustrative example.

Keywords: Coupled delayed neural networks; Bipartite synchronization; Event-triggered control (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:600:y:2022:i:c:s0378437122004046

DOI: 10.1016/j.physa.2022.127586

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