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Author Spotlight: Modular Neuronal Networks for Analyzing Brain Functions
Published on: June 7, 2024
Pinning bipartite synchronization for coupled reaction-diffusion neural networks with antagonistic interactions and
Baojun Miao1, Xuechen Li1, Jungang Lou2
1School of Science, Xuchang University, Xuchang 461000, China.
Abstract:
In this paper, the bipartite synchronization issue for a class of coupled reaction-diffusion networks with antagonistic interactions and switching topologies is investigated. First of all, by virtue of Lyapunov functional method and pinning control technique, we obtain some sufficient conditions which can guarantee that networks with signed graph topologies realize bipartite synchronization under any initial conditions and arbitrary switching signals. Secondly, for the general switching signal and periodic switching signal, a pinning controller that can ensure bipartite synchronization of reaction-diffusions networks is designed based on the obtained conditions. Meanwhile, a directed relationship between coupling strength and control gains is presented. Thirdly, numerical simulation is provided to demonstrate the correctness and validity of the derived theoretical results for reaction-diffusion systems. We briefly conclude our findings and future work.
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