{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,9]],"date-time":"2024-08-09T17:11:21Z","timestamp":1723223481172},"reference-count":15,"publisher":"World Scientific Pub Co Pte Ltd","issue":"10","funder":[{"name":"JSPS KAKENHI","award":["JP20K11957"],"award-info":[{"award-number":["JP20K11957"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Neur. Syst."],"published-print":{"date-parts":[[2021,10]]},"abstract":"<jats:p> Generation of useful variables and features is an important issue throughout the machine learning, artificial intelligence, and applied fields for their efficient computations. In this paper, the nearest neighbor relations are proposed for the minimal generation and the reduced variables of the functions in the threshold networks. First, the nearest neighbor relations are shown to be minimal and inherited for threshold functions and they play an important role in the iterative generation of the Chow parameters. Further, they give a solution for the Chow parameters problem. Second, convex cones are made of the nearest neighbor relations for the generation of the reduced variables. Then the edges of convex cones are compared for the discrimination of variables. Finally, the reduced variables based on the nearest neighbor relations are shown to be useful for documents classification. <\/jats:p>","DOI":"10.1142\/s0129065721500453","type":"journal-article","created":{"date-parts":[[2021,8,26]],"date-time":"2021-08-26T15:39:36Z","timestamp":1629992376000},"page":"2150045","source":"Crossref","is-referenced-by-count":1,"title":["Generation of Chow Parameters and Reduced Variables Through Nearest Neighbor Relations in Threshold Networks"],"prefix":"10.1142","volume":"31","author":[{"given":"Naohiro","family":"Ishii","sequence":"first","affiliation":[{"name":"Graduate School of Industrial Technology, Advanced Institute of Industrial Technology, Shinagawa-ku, Tokyo 140-0011, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tokuro","family":"Matsuo","sequence":"additional","affiliation":[{"name":"Graduate School of Industrial Technology, Advanced Institute of Industrial Technology, Shinagawa-ku, Tokyo 140-0011, Japan"},{"name":"Department of M-Commerce and Multimedia Applications, Asia University, Taichung 41354, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2021,8,25]]},"reference":[{"key":"S0129065721500453BIB001","volume-title":"Autocorrelation: A Principle for the Evaluation of Sensory Information by the Central Nervous System, Sensory Communication","author":"Reichard W.","year":"2012"},{"key":"S0129065721500453BIB002","doi-asserted-by":"publisher","DOI":"10.1137\/090756466"},{"key":"S0129065721500453BIB003","doi-asserted-by":"publisher","DOI":"10.1145\/2590772"},{"key":"S0129065721500453BIB004","doi-asserted-by":"publisher","DOI":"10.1109\/FOCS.1961.24"},{"key":"S0129065721500453BIB005","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-011-3534-4"},{"key":"S0129065721500453BIB006","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-015-7975-9_21"},{"key":"S0129065721500453BIB007","doi-asserted-by":"publisher","DOI":"10.3233\/FI-1997-303409"},{"key":"S0129065721500453BIB008","doi-asserted-by":"publisher","DOI":"10.3233\/ICA-2010-0345"},{"key":"S0129065721500453BIB009","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2682102"},{"key":"S0129065721500453BIB010","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-59650-1_33"},{"key":"S0129065721500453BIB011","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-48791-1_45"},{"key":"S0129065721500453BIB013","doi-asserted-by":"publisher","DOI":"10.1525\/9780520329560"},{"key":"S0129065721500453BIB014","first-page":"99","volume-title":"Linear Inequalities and Related Systems","author":"Fan K.","year":"1966"},{"key":"S0129065721500453BIB015","doi-asserted-by":"publisher","DOI":"10.1108\/eb046814"},{"key":"S0129065721500453BIB016","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1967.1053964"}],"container-title":["International Journal of Neural Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0129065721500453","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,17]],"date-time":"2021-09-17T10:34:43Z","timestamp":1631874883000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0129065721500453"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,25]]},"references-count":15,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2021,10]]}},"alternative-id":["10.1142\/S0129065721500453"],"URL":"https:\/\/doi.org\/10.1142\/s0129065721500453","relation":{},"ISSN":["0129-0657","1793-6462"],"issn-type":[{"value":"0129-0657","type":"print"},{"value":"1793-6462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,25]]}}}