Parameters identification problems for Hopfield-type neural network equations

This work is to discuss the identification problem of distributed parameter systems given by Hopfield-type neural network equations using classical optimal control theory. More rationally, we consider diffusion term in our model different from other models, in which the parameters appearing in diffusion term, linear term and nonlinear term. We prove the existence of optimal parameters and state the necessary conditions on optimizing parameters for the output error criterion give by quadratic cost.