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Several compensation schemes have been proposed to mitigate the updating error caused by nonlinearity; nevertheless, they usually involve complex peripheral circuits design. Herein, stochastic and adaptive learning methods for weight updating are developed, in which the inaccuracy caused by the memristor nonlinearity can be effectively suppressed. In addition, compared with the traditional nonlinear stochastic gradient descent (SGD) updating algorithm or the piecewise linear (PL) method, which are most often used in memristor neural network, the design is more hardware friendly and energy efficient without the consideration of pulse numbers, duration, and directions. Effectiveness of the proposed method is investigated on the training of LeNet\u20105 convolutional neural network. High accuracy, about 93.88%, on the Modified National Institute of Standards and Technology handwriting digits datasets is achieved (with typical memristor nonlinearity as \u00b11), which is close to the network with complex PL method (94.7%) and is higher than the original nonlinear SGD method (90.14%).<\/jats:p><\/jats:sec>","DOI":"10.1002\/aisy.202100041","type":"journal-article","created":{"date-parts":[[2021,7,5]],"date-time":"2021-07-05T03:21:52Z","timestamp":1625455312000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":52,"title":["Hardware\u2010Friendly Stochastic and Adaptive Learning in Memristor Convolutional Neural Networks"],"prefix":"10.1002","volume":"3","author":[{"given":"Wei","family":"Zhang","sequence":"first","affiliation":[{"name":"Guangxi Key Laboratory of Automatic Detecting Technology and Instrument Guilin University of Electronic Technology  Guilin 541004 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lunshuai","family":"Pan","sequence":"additional","affiliation":[{"name":"Research Center for Medical AI Shenzhen Institute of Advanced Technology Chinese Academy of Sciences  Shenzhen 518055 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuelong","family":"Yan","sequence":"additional","affiliation":[{"name":"Guangxi Key Laboratory of Automatic Detecting Technology and Instrument Guilin University of Electronic Technology  Guilin 541004 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangchao","family":"Zhao","sequence":"additional","affiliation":[{"name":"CNRS-International-NTU-THALES-Research-Alliance Nanyang Technological University  Singapore 639798 Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Chen","sequence":"additional","affiliation":[{"name":"Research Center for Medical AI Shenzhen Institute of Advanced Technology Chinese Academy of Sciences  Shenzhen 518055 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingli","family":"Wang","sequence":"additional","affiliation":[{"name":"CNRS-International-NTU-THALES-Research-Alliance Nanyang Technological University  Singapore 639798 Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Beng Kang","family":"Tay","sequence":"additional","affiliation":[{"name":"CNRS-International-NTU-THALES-Research-Alliance Nanyang Technological University  Singapore 639798 Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gaokuo","family":"Zhong","sequence":"additional","affiliation":[{"name":"Research Center for Medical AI Shenzhen Institute of Advanced Technology Chinese Academy of Sciences  Shenzhen 518055 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiangyu","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Materials Science and Engineering Guangdong Provincial Key Laboratory of Functional Oxide Materials and Devices Southern University of Science and Technology  Shenzhen 518055 Guangdong China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7794-3985","authenticated-orcid":false,"given":"Mingqiang","family":"Huang","sequence":"additional","affiliation":[{"name":"Research Center for Medical AI Shenzhen Institute of Advanced Technology Chinese Academy of Sciences  Shenzhen 518055 China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,7,5]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"LeCun Y.","year":"2015","journal-title":"Nature"},{"key":"e_1_2_9_3_1","first-page":"1097","volume":"25","author":"Krizhevsky A.","year":"2012","journal-title":"Adv. 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