Synchronization of Markov Switching Inertial Neural Networks with Mixed Delays under Aperiodically On-Off Adaptive Control

Beibei Guo () and Yu Xiao
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Beibei Guo: School of Mathematical Sciences, Hebei Normal University, Shijiazhuang 050024, China
Yu Xiao: Department of Mathematics, Harbin Institute of Technology, Harbin 150001, China

Mathematics, 2023, vol. 11, issue 13, 1-15

Abstract: In this paper, the issue of exponential synchronization in Markov switching inertial neural networks with mixed delays is investigated via aperiodically on–off adaptive control. The inertial term is considered, which extends the existing network modes with first-order differential term. Combined with the Lyapunov method, graph theory, and the differential inequalities technique, two types of synchronization criteria are presented which take into account all of the time delay information and reduce the conservativeness. Finally, some numerical simulations are provided in order to show the validity of the theoretical results.

Keywords: inertial neural networks; Markov switching; graph theory; aperiodically on–off adaptive control; exponential synchronization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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