On the stability of sets for reaction–diffusion Cohen–Grossberg delayed neural networks
Ivanka Stamova, Gani Tr. Stamov · Discrete and Continuous Dynamical Systems - S · 2020
In this paper, we introduce the notion of stability of sets for reaction-diffusion Cohen–Grossberg neural networks with time-varying delays. The Lyapunov–Razumikhin technique and a comparison principle are adapted to prove the new stability criteria. In addition, the obtained results are extended to the uncertain case, and the robust stability notion is also investigated. Examples are considered to demonstrate the effectiveness of our results.