The dense associative memory is one of the basic modern Hopfield networks and can store large numbers of memory patterns. This model stores given patterns as attractors in its dynamics. While the stationary state storage capacity has been investigated so far, its dynamical properties
have not been discussed. In this seminar, we briefly summarize the traditional Hopfield model and analyze the dynamics by means of an exact approach based
on generating functional analysis. It allows us to investigate convergence properties as well as the size of the attraction basins. We also analyze the stationary state of the updating rule.
reference:
[1] https://arxiv.org/abs/2506.00851