Stability criterion in Lagrange sense for complex-valued neural networks with mixed time-varying delays

In this paper, the global exponential stability in Lagrange sense for complex-valued neural networks with discrete time-varying delays and distributed time-varying delays is investigated. A criterion to ensure the global exponential stability in Lagrange sense for complex-valued neural networks with discrete time-varying delays and distributed time-varying delays is obtained by employing Lyapunov-Krasovskii functional and using free-weighting-matrix approach and matrix inequality techniques. The condition is expressed in complex-valued linear matrix inequalities, which can be checked numerically using the effective YALMIP toolbox in MATLAB.