Synchronization and anti-synchronization for complex-valued inertial neural networks with time-varying delays

In this article, synchronization and anti-synchronization problems of complex-valued inertial neural networks with time-varying delays are studied. Firstly, the complex-valued inertial neural networks model is expressed as the first-order complex-valued differential system through the method of variable substitution. Then, via constructing the appropriate Lyapunov functional and using linear matrix inequalities (LMIs) approach, some sufficient conditions to ensure the synchronization and anti-synchronization of the considered system are established. Finally, numerical examples are given to demonstrate the effectiveness of the proposed results. (C) 2021 Elsevier Inc. All rights reserved.

Automated summary

This article studies the synchronization and anti-synchronization problems of complex-valued inertial neural networks with time-varying delays. By expressing the network model as a first-order complex-valued differential system and using Lyapunov functional and LMIs approach, sufficient conditions for synchronization and anti-synchronization are established. Numerical examples are provided to demonstrate the effectiveness of the proposed results.