A new LMI condition for delay-dependent asymptotic stability of delayed Hopfield neural networks
Shengyuan Xu, James Lam, Daniel W. C. Ho · IEEE Transactions on Circuits and Systems II Analog and Digital Signal Processing · 2006
In this paper, a new delay-dependent asymptotic stability condition for delayed Hopfield neural networks is given in terms of a linear matrix inequality, which is less conservative than existing ones in the literature. This condition guarantees the existence of a unique equilibrium point and its global asymptotic stability of a given delayed Hopfield neural network. Examples are provided to show the reduced conservatism of the proposed condition.