Global asymptotic stability for neutral-type Hopfield neural networks with multiple delays

Abstract

Abstract This paper aims to study stability problem for neutral-type Hopfield neural networks including multiple time delays in states and multiple neutral delays in time derivative of states. The stability criteria cannot be derived by linear matrix inequality since the networks cannot be transformed into the vector-matrix form. By constructing LyapunovKrasovskii functional and using inequality techniques, novel stability criteria of global asymptotic stability are established. Finally, an example is given to show the effectiveness of the theoretical result.