Optimisation of Hopfield networks for storage and recall: a decade review
by Jay Kant Pratap Singh Yadav; Arun Kumar Yadav; Divakar Yadav; Vikash Yadav
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 21, No. 3/4, 2022

Abstract: Pattern storage and recall in an efficient and effective manner is a prominent task in the pattern recognition field. Recurrent (also called feedback) networks are most frequently used network that can store and recall the patterns. Recurrent networks have a capability of recalling noisy or partial patterns like brain. A detailed study of different neural network, it is found that Hopfield neural network outperforms as compared to others. In this paper, we illustrate the review of a decade on optimisation of Hopfield neural network to improve storage capacity and recalling of patterns.

Online publication date: Tue, 12-Apr-2022

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