An estimation of upperbound of delays for global asymptotic stability of delayed Hopfield neural networks

This paper provides an upperbound of delays for the global asymptotic stability of the equilibrium of Hopfield neural networks with transmission delays. Such a bound has important significance in both theory and application for the design of the globally stable networks. An example is also given to illustrate that the conditions of our result are feasible.