Global lagrange stability of complex-valued neural networks with time-varying delays

In this article, the global exponential stability in Lagrange sense for complex-valued neural networks (CVNNs) with time-varying delays is investigated under the condition that the activation functions are assumed to satisfy the globally Lipschitz condition in the complex domain. By constructing appropriate Lyapunov-Krasovskii functionals, a delay-dependent sufficient condition is provided to ascertain the considered CVNNs to be globally exponentially stable in Lagrange sense.