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Comparative Analysis of Recurrent Networks for Pattern Storage and Recalling of Static Images

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Jay Kant Pratap Singh Yadav, Laxman Singh, Zainul Abdin Jaffery
10.5120/ijca2017914918

Jay Kant Pratap Singh Yadav, Laxman Singh and Zainul Abdin Jaffery. Comparative Analysis of Recurrent Networks for Pattern Storage and Recalling of Static Images. International Journal of Computer Applications 170(10):15-19, July 2017. BibTeX

@article{10.5120/ijca2017914918,
	author = {Jay Kant Pratap Singh Yadav and Laxman Singh and Zainul Abdin Jaffery},
	title = {Comparative Analysis of Recurrent Networks for Pattern Storage and Recalling of Static Images},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2017},
	volume = {170},
	number = {10},
	month = {Jul},
	year = {2017},
	issn = {0975-8887},
	pages = {15-19},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume170/number10/28106-2017914918},
	doi = {10.5120/ijca2017914918},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Auto associative memory is widely used network for pattern storage and recalling of patterns. Hopfield network, Hamming network are popularly known auto associative memory networks. In this paper we present comparative analysis in term of storage and recalling efficiency of Hopfield network and Hamming network and we choose images of letters. The results of the simulation for Hopfield and hamming network for character recognition under high noise are delineated and mentioned.

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Keywords

Auto associative, Pattern, Recurrent network, Hebbian rule