Finite-time and fixed-time synchronization of fuzzy Clifford-valued Cohen-Grossberg neural networks with discontinuous activations and time-varying delays

In this article, we are concerned with fuzzy Clifford-valued Cohen-Grossberg neural networks (FCVCGNNs) via discontinuous activations and time-varying delays. First, the time-delayed feedback strategy is used to investigate the synchronization in finite-time and fixed-time of FCVCGNNs with discontinuous activations and time-varying delays. By designing Lyapunov functions and utilizing differential inequalities, several effective conditions are derived to ensure synchronization in finite-time and fixed-time of the addressed neural networks. A novel fixed-time convergence method is proposed to study synchronization in fixed-time of discontinuous delayed FCVCGNNs. Furthermore, the settling time of synchronization are estimated. In the end, two numerical examples with simulations are given to confirm the effectiveness of the synchronization criteria.