Global asymptotic stability and projective lag synchronization for uncertain inertial competitive neural networks

Abstract

Without converting the second-order term into the first-order term, the global asymptotic stability and projective lag synchronization problem of the second-order uncertain competitive neural networks with infinite distribution and time-varying delay are studied by designing an adaptive control scheme. Based on Lyapunov stability theory, some new criteria are directly obtained according to algebraic inequalities, so as to ensure the stability and projective lag synchronization of uncertain competitive neural networks. In addition, compared with the reduced order method, the projective lag synchronization is obtained directly by using the non-reduced-order method to construct some Lyapunov functions. Finally, some examples are provided to determine the availability of theoretical results.