Global stability of complex-valued recurrent neural networks with both mixed time delays and impulsive effect

The global stability problem for a class of complex-valued neural networks with both mixed time delays and impulsive effect is concerned in this literature. By using Schur complement, forming an equivalent matrix, and constructing an appropriate Lyapunov functional, some new sufficient criteria to ascertain the existence, uniqueness, globally exponential stability and globally asymptotical stability of the equilibrium point of complex-valued neural networks are obtained in terms of linear matrix inequality techniques. Meanwhile, several linear matrix inequalities have been proved in the literature, which shall be used to prove the stability of the equilibrium point. Finally, simulation results of one numerical example are also delineated to demonstrate the effectiveness of our theoretical results.