Delayed distributed impulsive synchronization of coupled neural networks with mixed couplings

In this paper, synchronization problem of coupled neural networks (CNNs) with both the distributed delay coupling (DDC) and the nonlinear coupling is studied. Firstly, a novel array of delayed inequalities with mixed delays is introduced. Specifically, mixed delays involve the distributed delay and discrete impulsive delays. Stemmed from such newly proposed inequalities, some sufficient conditions ensuring the exponential synchronization of CNNs are obtained by utilizing technique of linear matrix inequalities (LMIs) and Kronecker product. Furthermore, the delay-dependent distributed impulsive controller is devised, where discrete delays can be nonidentical at different impulsive instants. In addition, we pay special attention on synchronization issue of large-scale CNNs and derive some low-dimensional sufficient conditions by employing the technique of the matrix decomposition. Finally, two illustrative numerical examples are provided to demonstrate the effectiveness of theoretical results. (c) 2022 Elsevier B.V. All rights reserved.

Automated summary

This paper studies the synchronization problem of coupled neural networks with distributed delay coupling and nonlinear coupling. By introducing a novel array of delayed inequalities with mixed delays, some sufficient conditions ensuring exponential synchronization are obtained using linear matrix inequalities (LMIs) and Kronecker product. Furthermore, a delay-dependent distributed impulsive controller is proposed, and low-dimensional sufficient conditions are derived using the matrix decomposition technique.