New criteria on periodicity and stabilization of discontinuous uncertain inertial Cohen-Grossberg neural networks with proportional delays

This paper is concerned with the periodicity and stabilization of a class of discontinuous uncertain inertial Cohen-Grossberg neural networks with proportional delays. First of all, based on the differential inclusions and coincidence theorem, some new proportional delay-dependent criteria are obtained for ensuring the existence of periodic solutions. It is the first result on the proportional delay-dependent criteria of delayed inertial neural networks (INNs). Secondly, in light of the definition of fixed-time (FXT) stable, the zero solution of the considered inertial neural model can achieve the FXT stabilization with the help of the designed discontinuous control laws. Finally, for the purpose of examining the correctness of the established results, one numerical example and illustrative simulations are provided.