Robust stability criteria for neural Cohen-Grossberg networks with both time-varying delay and parametric uncertainties

In this paper, a stability analysis of a Cohen-Grossberg neural network (CGNN) with both time-varying delays and parametric uncertainties is given by employing Lyapunov-Krasovskii functional, delay partitioning method and free matrix approach. A sufficient condition is derived to ensure the stability of the uncertain CGNN with time-delay. It is noticeable that the theorem derived in this paper does not require the derivative of time-delay, which makes the result more general compared with former works. Besides, the lower bound of time-delay is also considered in this paper, which may lead to a less conservative result.