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The dynamic properties of a class of neural networks (which includes the Hopfield model as a special case) are investigated by studying the qualitative behavior of equilibrium points. The results fall into one of two categories: results pertaining to analysis (e.g., stability properties of an equilibrium, asymptotic behavior of solutions, etc.) and results pertaining to synthesis (e.g. the design of a neural network with prespecified equilibrium points which are asymptotically stable). Most (but not all) of the results presented are global, and their applicability is demonstrated by an example.>
Li et al. (Fri,) studied this question.