Stability analysis of fractional reaction-diffusion memristor-based neural networks with neutral delays via Lyapunov functions

In the realm of stability analysis for fractional neutral neural networks, it is not uncommon to encounter erroneous Lyapunov functions. To investigate the stability of fractional memristor-based neural networks with neutral delays and reaction–diffusion (FNRDMNNs), this study presents a novel modified Lyapunov–Krasovskii functions. By invoking Green's theorem and employing inequality techniques, we derive two nonconservative criteria and a corollary through the design of two enhanced pinning controllers, ensuring the stability of FNRDMNNs. Furthermore, the contributions of this paper not only serve as refinements to existing findings but also hold broader applicability for advancing the theoretical analysis of fractional neutral-type systems. To corroborate the obtained results, we perform a series of simulations.