This paper presents a contribution to the use of Hopfield neural networks (HNNs) for parameter estimation. Our focus is on time-invariant systems that are linear in the parameters. We introduce a suitable HNN and present a weaker condition than the currently existing ones that guarantees the convergence of the parameterization estimated by the network to the actual parameterization. The application of our results is illustrated in a parameter estimation problem for a two carts system
