Fixed-time stabilization control of reaction-diffusion Cohen-Grossberg neural networks

This paper focus on the fixed-time stabilization control strategy of delayed Cohen-Grossberg neural networks with reaction-diffusion terms. By a new agency of Hardy-Poincarè inequality and some analysis techniques, some testable results on the fixed-time stabilization control of the target model were summarized, which depend on the system parameters, reaction-diffusion coefficients as well as the regional feature. The results obtained in this paper presented a more precise estimation compared to many known results. Finally, an example and its simulations are exhibited to explain our findings.