{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T07:45:54Z","timestamp":1780991154841,"version":"3.54.1"},"reference-count":42,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["92364202"],"award-info":[{"award-number":["92364202"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Chinese Academy of Sciences (CAS) Strategic Leading Science and Technology Project","doi-asserted-by":"publisher","award":["XDB44000000"],"award-info":[{"award-number":["XDB44000000"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/access.2025.3535786","type":"journal-article","created":{"date-parts":[[2025,1,28]],"date-time":"2025-01-28T18:46:46Z","timestamp":1738090006000},"page":"66686-66699","source":"Crossref","is-referenced-by-count":1,"title":["NeuAFG: Neural Network-Based Analog Function Generator for Inference in CIM"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-5744-8437","authenticated-orcid":false,"given":"Pengcheng","family":"Feng","sequence":"first","affiliation":[{"name":"Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yihao","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinke","family":"Yu","sequence":"additional","affiliation":[{"name":"Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhelong","family":"Jiang","sequence":"additional","affiliation":[{"name":"Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junjia","family":"Su","sequence":"additional","affiliation":[{"name":"Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qian","family":"Zhou","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Yue","sequence":"additional","affiliation":[{"name":"Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhigang","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haifang","family":"Jian","sequence":"additional","affiliation":[{"name":"Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5928-9705","authenticated-orcid":false,"given":"Huaxiang","family":"Lu","sequence":"additional","affiliation":[{"name":"Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7990-9855","authenticated-orcid":false,"given":"Wan\u2019Ang","family":"Xiao","sequence":"additional","affiliation":[{"name":"Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3157-0172","authenticated-orcid":false,"given":"Gang","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/7068349"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2013.2244083"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-81-322-3972-7_19"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001139"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3579371.3589062"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001140"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3352460.3358328"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ISCA45697.2020.00073"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1049\/el.2012.0253"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TCSII.2019.2891688"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1002\/cta.488"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JXCDC.2020.2981048"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2020.3034856"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2023.3303910"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TCSI.2018.2841039"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TCSII.2023.3298910"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2021.3107252"},{"key":"ref18","first-page":"356","article-title":"Multilayered feedforward networks are universal approximators","volume":"2","author":"Stinchcomb","year":"1989","journal-title":"Neural Netw."},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/LED.2019.2936261"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/mi12101183"},{"key":"ref21","article-title":"Fast and accurate deep network learning by exponential linear units (ELUs)","author":"Clevert","year":"2015","journal-title":"arXiv:1511.07289"},{"key":"ref22","article-title":"Gaussian error linear units (GELUs)","author":"Hendrycks","year":"2016","journal-title":"arXiv:1606.08415"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ieecon53204.2022.9741701"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1908.08681"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2023.3319711"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVIDLICCEA56201.2022.9824846"},{"key":"ref27","first-page":"1","article-title":"ResNet with one-neuron hidden layers is a universal approximator","volume-title":"Proc. Adv. neural Inf. Process. Syst.","volume":"31","author":"Lin"},{"key":"ref28","article-title":"Critical hyper-parameters: No random, no cry","author":"Bousquet","year":"2017","journal-title":"arXiv:1706.03200"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.01.007"},{"key":"ref30","first-page":"2184","article-title":"Towards understanding the condensation of neural networks at initial training","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhou"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1038\/s41928-024-01228-7"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2020.2989373"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref36","article-title":"MobileViT: Light-weight, general-purpose, and mobile-friendly vision transformer","author":"Mehta","year":"2021","journal-title":"arXiv:2110.02178"},{"key":"ref37","first-page":"10347","article-title":"Training data-efficient image transformers & distillation through attention","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Touvron"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3253668"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICM.2017.8268866"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2015.2472599"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TCSI.2019.2939563"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10820123\/10856149.pdf?arnumber=10856149","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T17:42:25Z","timestamp":1745343745000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10856149\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":42,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3535786","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}