A fractional Halanay inequality for neutral systems and its application to Cohen-Grossberg neural networks

We expand the Halanay inequality to accommodate fractional-order systems incorporating both discrete and distributed neutral delays. By establishing specific conditions, we demonstrate that the solutions of these systems converge to zero at a Mittag-Leffler rate. Our analysis is versatile, accommodating a wide range of delay kernels. This versatility extends the applicability of our findings to fractional Cohen-Grossberg neural networks, offering valuable insights into their stability and dynamical behavior.