Cloud Hopfield neural network: Analysis and simulation

In this paper we present modifications in the dynamics of Hopfield neural network. We compare our modified retrieval algorithms with both synchronous and asynchronous retrieval algorithms used in Hopfield dynamics. Our results show that a modified Hopfield neural network consisting of a cloud with r number of unique neurons, (in the simulation given in this paper r=3% i.e. 4 neurons out of total 120) is better in terms of both retrieval capabilities and convergence time in comparison to the asynchronous retrieval algorithm. Moreover, unlike synchronous retrieval algorithm it does not enter oscillation states.