{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T15:52:06Z","timestamp":1649173926609},"reference-count":0,"publisher":"World Scientific Pub Co Pte Lt","issue":"08","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[1996,12]]},"abstract":"<jats:p> In this paper the Bipolar Random Network is described, which constitutes an extension of the Random Neural Network model and exhibits autoassociative memory capabilities. This model is characterized by the existence of positive and negative nodes and symmetrical behavior of positive and negative signals circulating in the network. The network's ability of acting as autoassociative memory is examined and several techniques are developed concerning storage and reconstruction of patterns. These approaches are either based on properties of the network or constitute adaptations of existing neural network techniques. The performance of the network under the proposed schemes has been investigated through experiments showing very good storage and reconstruction capabilities. Moreover, the scheme exhibiting the best behavior seems to outperform other well-known associative neural network models, achieving capacities that exceed 0.5n where n is the size of the network. <\/jats:p>","DOI":"10.1142\/s0218001496000529","type":"journal-article","created":{"date-parts":[[2004,9,6]],"date-time":"2004-09-06T11:50:09Z","timestamp":1094471409000},"page":"919-937","source":"Crossref","is-referenced-by-count":2,"title":["HIGH CAPACITY ASSOCIATIVE MEMORY BASED ON THE RANDOM NEURAL NETWORK MODEL"],"prefix":"10.1142","volume":"10","author":[{"given":"ARISTIDIS","family":"LIKAS","sequence":"first","affiliation":[{"name":"National Technical University of Athens, Department of Electrical and Computer Engineering, 157 73 Zographou, Athens, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"ANDREAS","family":"STAFYLOPATIS","sequence":"additional","affiliation":[{"name":"National Technical University of Athens, Department of Electrical and Computer Engineering, 157 73 Zographou, Athens, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2012,4,30]]},"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001496000529","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T16:59:46Z","timestamp":1565110786000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218001496000529"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1996,12]]},"references-count":0,"journal-issue":{"issue":"08","published-online":{"date-parts":[[2012,4,30]]},"published-print":{"date-parts":[[1996,12]]}},"alternative-id":["10.1142\/S0218001496000529"],"URL":"https:\/\/doi.org\/10.1142\/s0218001496000529","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"value":"0218-0014","type":"print"},{"value":"1793-6381","type":"electronic"}],"subject":[],"published":{"date-parts":[[1996,12]]}}}