Stability analysis for neutral-type Cohen-Grossberg neural networks with multiple delays

Inhalt:
This article is concerned with global asymptotic stability of neutral-type Cohen-Grossberg neural networks (CGNNs) with multiple delays. Linear matrix inequality method is invalid because such networks cannot be transformed into the vector-matrix form. By using Lyapunov-Krasovskii functional and inequality techniques, novel stability criteria are established. The proposed criteria are delay-independent and depend on the coefficients of neutral delays. An example is given to show the effectiveness of the theoretical result.