https://doi.org/10.1140/epjs/s11734-025-01909-0
Regular Article
Predefined-time synchronization for extended memristive competitive neural networks with varied leakage delays
1
School of Mathematics and Systems Science, Guangdong Polytechnic Normal University, 510665, Guangzhou, China
2
College of Science, North China University of Technology, 100144, Beijing, China
3
Potsdam Institute for Climate Impact Research, 14473, Potsdam, Germany
4
Institute of Physics, Humboldt University, 12489, Berlin, Germany
a
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Received:
13
March
2025
Accepted:
2
September
2025
Published online:
7
September
2025
Abstract
In practical applications, there is the important problem: Can we make a system synchronize in any given time or hopeful time? In order to estimate the smaller upper bound of synchronization time, the predefined-time synchronization (PdT synchronization) of a class of extended memristive competitive neural networks(eMCNNs) with varied leakage delays is studied here. Through designing suitable controllers and inequality techniques, synchronization of eMCNNs with varied leakage delays can be indeed reached in a predefined time. Novel criteria of PdT synchronizations of this model are built to guarantee the PdT synchronization of eMCNNs with varied leakage delays. Finally, a numerical example shows the usefulness of our theoretical results and the explored effects of varied leakage delays on the PdT synchronization of eMCNNs with varied leakage delays.
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© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
