Study of Hopfield neural network with sub-optimal and random GA for pattern recalling of English characters

Authors:
Somesh Kumar;Manu Pratap Singh
Affiliations:
Noida Institute of Engineering and Technology, Greater Noida, Uttar Pradesh, India;Department of Computer Science, Institute of Computer and Information Science, Dr. B.R. Ambedkar University, Khandari Campus, Agra, Uttar Pradesh, India
Venue:
Applied Soft Computing
Year:
2012

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Abstract

In this paper we are studying the performance of Hopfield neural network for recalling of memorized patterns from the Hebbian rule and genetic algorithm for English characters. In this process the genetic algorithm is employed in random form and sub-optimal form for recalling of memorized patterns corresponding to the presented noisy prototype input patterns. The objective of this study is to determine the optimal weight matrix for correct recalling corresponding to noisy form of the English characters. In this study the performance of neural network is evaluated in terms of the rate of success for recalling of noisy input patterns of the English characters with GA in two aspects. The first aspect reflects the random nature of the GA and the second one exhibits the suboptimal nature of the GA for its exploration. The simulated results demonstrate the better performance of network for recalling of the stored letters of English alphabets using genetic algorithm on the suboptimal weight matrix.