THE QUANTITATIVE ANALYSIS OF STOCHASTIC HOPFIELD NEURAL NETWORK MODEL

In this paper, the effect of input noise on the typical stochastic Hopfield neural network modei is discussed. It is shown that the expectation of the stochastic HNN of the trajectory is uniformly bounded over time. For practical design purposes, the stochastic input error estimates for the stochastic HNN with respect to the corresponding deterministic HNN is derived. In addition, the designer can use these results to constrain the design space so that the achieved design satisnes the performance specifications whenever possible.