On the storage capacity of the Hopfield model with biased patterns
We introduce a form of the Hopfield model that is able to store an increasing number of biased i.i.d. patterns (it is well known that the standard Hopfield model fans to work properly in this contest). We show that this new form of the Hopfield model with N neurons can store N/gamma log N or alpha N biased patterns (depending on which notion of storage is used). The quantity gamma increases with an increasing bias of the patterns, while alpha decreases when the bias gets large.
storage capacity hopfield model large deviations neural networks