title: The asymptotic memory capacity of the generalized Hopfield network.
abstract: This paper presents a theoretical analysis on the asymptotic memory capacity of the generalized Hopfield network. The perceptron learning scheme is proposed to store sample patterns as the stable states in a generalized Hopfield network. We have obtained that (n-1) and 2n are a lower and an upper bound of the asymptotic memory capacity of the network of n neurons, respectively, which shows that the generalized Hopfield network can store the larger number of sample patterns than Hopfield network.
authors.affiliation: Institute of Mathematics, Shantou University, Shantou, Guangdoug, People's Republic of China
authors.forename: Jinwen
authors.initials: J
authors.lastname: Ma