 Output synchronization of reaction-diffusion neural networks with multiple output couplings via generalized intermittent controlZhuoyuan Huang and Haibo Bao Applied Mathematics and Computation, 2024, vol. 477, issue C Abstract: This paper specializes in exponential output synchronization of reaction-diffusion neural networks (RDNNs) for two different cases of output couplings. The proposed model is novel for incorporating multiple output couplings related to their own output states as well as output spatial diffusion couplings in the absence of ordinary differential equations (ODE) systems. Generalized intermittent control based on spatial sampled-data is adopted for the first time to handle error systems consisting of the states of RDNNs with different output couplings scenarios and the average of the sum of their output states to achieve exponential stability. Some sufficient conditions for determining the proposed network models are established by control protocols based on the Lyapunov functional method. Finally, the obtained theoretical results are demonstrated to be valid by numerical simulations. Keywords: Output synchronization; Reaction-diffusion neural networks; Intermittent control; Output couplings (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:477:y:2024:i:c:s0096300324002832 DOI: 10.1016/j.amc.2024.128822 Access Statistics for this article Applied Mathematics and Computation is currently edited by Theodore Simos More articles in Applied Mathematics and Computation from Elsevier |
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