{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T09:27:43Z","timestamp":1771493263267,"version":"3.50.1"},"reference-count":0,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[1997,11,1]],"date-time":"1997-11-01T00:00:00Z","timestamp":878342400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[1997,11]]},"abstract":"<jats:p>We extend the theory of nonsingleton fuzzy logic systems (NSFLSs) by presenting an algorithm to design and train such systems. Since NSFLSs are a generalization of singleton fuzzy logic systems, the algorithm is equally applicable to both types of systems. The proposed SVD-QR method selects subsets of independent basis functions which are sufficient to represent a given system, through operations on a nonsingleton fuzzy basis function matrix. In addition, it provides an estimate of the number of necessary basis functions. We present several examples to illustrate the ability of the SVD-QR method to operate in uncertain environments.<\/jats:p>","DOI":"10.3233\/ifs-1997-5408","type":"journal-article","created":{"date-parts":[[2019,12,2]],"date-time":"2019-12-02T17:39:24Z","timestamp":1575308364000},"page":"367-374","source":"Crossref","is-referenced-by-count":21,"title":["A Singular-Value-QR Decomposition Based Method for Training Fuzzy Logic Systems in Uncertain Environments"],"prefix":"10.1177","volume":"5","author":[{"given":"George C.","family":"Mouzouris","sequence":"first","affiliation":[{"name":"Signal and Image Processing Institute, Department of Electrical Engineering-Systems, University of Southern California, Los Angeles, CA 90089-2564, USA"}]},{"given":"Jerry M.","family":"Mendel","sequence":"additional","affiliation":[{"name":"Signal and Image Processing Institute, Department of Electrical Engineering-Systems, University of Southern California, Los Angeles, CA 90089-2564, USA"}]}],"member":"179","published-online":{"date-parts":[[1997,11]]},"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-1997-5408","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-1997-5408","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T08:38:31Z","timestamp":1771490311000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/IFS-1997-5408"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1997,11]]},"references-count":0,"journal-issue":{"issue":"4","published-print":{"date-parts":[[1997,11]]}},"alternative-id":["10.3233\/IFS-1997-5408"],"URL":"https:\/\/doi.org\/10.3233\/ifs-1997-5408","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[1997,11]]}}}