{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,6]],"date-time":"2022-04-06T02:44:02Z","timestamp":1649213042051},"reference-count":0,"publisher":"World Scientific Pub Co Pte Lt","issue":"01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Neur. Syst."],"published-print":{"date-parts":[[1992,1]]},"abstract":"<jats:p> WIS-ART merges the self-organising properties of Adaptive Resonance Theory (ART) with the operation of WISARD, an adaptive pattern recognition machine which uses discriminators of conventional Random Access Memories (RAMs). The result is an unsupervised pattern clustering system operating at near real-time that implements the leader algorithm. ART\u2019s clustering is highly dependent upon the value of a \u201cvigilance\u201d parameter, which is set prior to training. However, for WIS-ART hierarchical clustering is performed automatically by the partitioning of discriminators into \u201cmulti-vigilance modules\u201d. Thus, clustering may be controlled during the test phase according to the degree of discrimination (hierarchical level) required. Methods for improving the clustering characteristics of WIS-ART whilst still retaining stability are discussed. <\/jats:p>","DOI":"10.1142\/s0129065792000061","type":"journal-article","created":{"date-parts":[[2004,11,24]],"date-time":"2004-11-24T03:29:42Z","timestamp":1101266982000},"page":"57-63","source":"Crossref","is-referenced-by-count":3,"title":["WIS-ART: UNSUPERVISED CLUSTERING WITH RAM DISCRIMINATORS"],"prefix":"10.1142","volume":"03","author":[{"given":"Eamon P.","family":"Fulcher","sequence":"first","affiliation":[{"name":"Neural Systems Engineering Laboratory, Department of Electrical Engineering, Imperial College of Science, Technology and Medicine, London SW7, UK"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"container-title":["International Journal of Neural Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0129065792000061","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T01:54:05Z","timestamp":1565142845000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0129065792000061"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1992,1]]},"references-count":0,"journal-issue":{"issue":"01","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[1992,1]]}},"alternative-id":["10.1142\/S0129065792000061"],"URL":"https:\/\/doi.org\/10.1142\/s0129065792000061","relation":{},"ISSN":["0129-0657","1793-6462"],"issn-type":[{"value":"0129-0657","type":"print"},{"value":"1793-6462","type":"electronic"}],"subject":[],"published":{"date-parts":[[1992,1]]}}}