Global exponential stability of complex-valued neural networks with time-varying delays on time scales

Abstract

In this paper, the global exponential stability of complex-valued neural networks (CVNN) with time-varying delays is investigated. By constructing appropriate Lyapunov-Krasovskii functionals and using matrix inequality technique, a new delay-dependent criterion for checking the global exponential stability of the addressed CVNN is established in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. An example with simulations is given to show the effectiveness of the proposed criterion.