首页|Finite-time bipartite synchronization of coupled neural networks with uncertain parameters
Finite-time bipartite synchronization of coupled neural networks with uncertain parameters
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NSTL
Elsevier
This paper investigates the finite-time bipartite synchronization (FTBS) of coupled neural networks (CNNs) with uncertain parameters. Under signed graphs, two control strategies are designed to guarantee FTBS of CNNs with or without external disturbances, respectively. For the disturbed CNNs, a discontinuous adaptive control strategy is proposed to overcome the impacts caused by uncertain parameters and disturbances with the help of non-smooth analysis and Lyapunov stability theory. For the undisturbed CNNs, a periodically intermittent adaptive control strategy is developed to achieve FTBS. Finally, two numerical examples are provided to demonstrate the effectiveness of theoretical results. (C) 2021 Elsevier B.V. All rights reserved.
NSTL
Elsevier
