{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:36:36Z","timestamp":1777703796406,"version":"3.51.4"},"reference-count":30,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2018,7,9]],"date-time":"2018-07-09T00:00:00Z","timestamp":1531094400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2018,7,27]]},"abstract":"<jats:p>\n                    In order to solve the problem of unstable sparseness of non-negative matrix factorization (NMF), the improved NMF algorithms with\n                    <jats:italic>L<\/jats:italic>\n                    <jats:sub>0<\/jats:sub>\n                    sparseness constraints are proposed. With the constraining the\n                    <jats:italic>L<\/jats:italic>\n                    <jats:sub>0<\/jats:sub>\n                    norm of the coefficient matrix, we applied inverse matching principle into non-negative least square (ISNNLS) which enhances the reconstruction ability of the decomposition matrix. In addition, the\n                    <jats:italic>L<\/jats:italic>\n                    <jats:sub>0<\/jats:sub>\n                    sparseness constraints are added to the basis matrix. In the updating process, the proposed algorithm set the smallest value to zero by projecting the basis vectors onto the closest non-negative vector with the expected sparseness. The experimental results have illustrated that the proposed algorithm can achieve higher reconstruction quality and effectiveness compared with the other algorithms.\n                  <\/jats:p>","DOI":"10.3233\/jifs-171116","type":"journal-article","created":{"date-parts":[[2018,7,10]],"date-time":"2018-07-10T14:37:09Z","timestamp":1531233429000},"page":"729-737","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Non-negative matrix factorization with\n                    <i>L<\/i>\n                    <sub>0<\/sub>\n                    sparseness constraints and its applications to face recognition"],"prefix":"10.1177","volume":"35","author":[{"given":"Dong","family":"Han","sequence":"first","affiliation":[{"name":"School of Information Enginering, Nanchang Hangkong University, Nanchang, China"}]},{"given":"Shan","family":"Gai","sequence":"additional","affiliation":[{"name":"School of Information Enginering, Nanchang Hangkong University, Nanchang, China"}]}],"member":"179","published-online":{"date-parts":[[2018,7,9]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1038\/44565"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.3724\/SP.J.1146.2011.01117"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.3724\/SP.J.1146.2010.00212"},{"issue":"7","key":"e_1_3_2_5_2","first-page":"1425","article-title":"Image segmentation of white matter based on local Walsh transform and non-negative matrix factorization","volume":"23","author":"Zhao H.F.","year":"2012","unstructured":"ZhaoH.F., LiQ.C., BinL. , Image segmentation of white matter based on local Walsh transform and non-negative matrix factorization, Guangdianzi Jiguang\/Journal of Optoelectronics Laser 23(7) (2012), 1425\u20131430.","journal-title":"Guangdianzi Jiguang\/Journal of Optoelectronics Laser"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1049\/el.2010.3239"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.231"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2011.01.012"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1049\/iet-cvi.2013.0055"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2008.918957"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1162\/jocn.1991.3.1.71"},{"key":"e_1_3_2_12_2","first-page":"281","article-title":"Some methods for classification and analysis of multivariate observations,(1), pp","author":"MacQueen J.","year":"1967","unstructured":"MacQueenJ., Some methods for classification and analysis of multivariate observations,(1), pp, Proc 5th Berkeley Symp Math Stat (1967), 281\u2013297.","journal-title":"Proc 5th Berkeley Symp Math Stat"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0437847100"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2005.864420"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1137\/070709967"},{"key":"e_1_3_2_16_2","doi-asserted-by":"crossref","unstructured":"MorupM. 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