Abstract
This paper focus on the synchronization of complex-valued neural networks (CVNNs) with both discrete and distributed two additive time-varying delays. By applying matrix inequality technique and exploiting reciprocally convex approach, several delay-dependent criteria are presented in the form of linear matrix inequalities (LMIs) to ensure the global synchronization of CVNNs via structuring an appropriate Lyapunov-Krasovskii functional. An example with simulations is provided to ensure the feasibility of the obtained result. (C) 2019 Elsevier B.V. All rights reserved.