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Finally, the performance status of TFI could be identified by the softmax classifier with Adam optimizer. Several groups of experiments have been studied when the BLDCM under different operating conditions. The results show that the fusion features can get a higher degree of discrimination so as to the presented network model also obtains better classification accuracy, which verify the feasibility and superiority to the other networks.<\/jats:p>","DOI":"10.1007\/s40747-021-00337-6","type":"journal-article","created":{"date-parts":[[2021,4,3]],"date-time":"2021-04-03T20:02:28Z","timestamp":1617480148000},"page":"29-42","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":51,"title":["Adaptive feature extraction and fault diagnosis for three-phase inverter based on hybrid-CNN models under variable operating conditions"],"prefix":"10.1007","volume":"8","author":[{"given":"Quan","family":"Sun","sequence":"first","affiliation":[]},{"given":"Xianghai","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Hongsheng","family":"Li","sequence":"additional","affiliation":[]},{"given":"Jisheng","family":"Fan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,4,3]]},"reference":[{"key":"337_CR1","doi-asserted-by":"publisher","first-page":"4367","DOI":"10.1007\/s12206-020-1002-x","volume":"34","author":"AH Aljemely","year":"2020","unstructured":"Aljemely AH, Xuan J, Jawad FKJ et al (2020) A novel unsupervised learning method for intelligent fault diagnosis of rolling element bearings based on deep functional auto-encoder [J]. 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