In this paper a recurrent network, which consists of O(√m log m) RBF (radial basis functions)units with maximum norm employing any activation function that has different values in at least two nonnegative points, is constructed so as to implement a given deterministic finite automaton with m states the underlying simulation proves to be robust with respect to analog noise for a large class of smooth activation functions with a special type of inflexion.