{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T15:56:23Z","timestamp":1758815783249,"version":"3.37.3"},"reference-count":51,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["41871302"],"award-info":[{"award-number":["41871302"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Development Program of China","award":["2018YFB1004600"],"award-info":[{"award-number":["2018YFB1004600"]}]},{"DOI":"10.13039\/501100003995","name":"Anhui Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["2108085J19"],"award-info":[{"award-number":["2108085J19"]}],"id":[{"id":"10.13039\/501100003995","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst."],"published-print":{"date-parts":[[2022,8]]},"DOI":"10.1109\/tcad.2021.3108706","type":"journal-article","created":{"date-parts":[[2021,8,30]],"date-time":"2021-08-30T21:16:10Z","timestamp":1630358170000},"page":"2598-2610","source":"Crossref","is-referenced-by-count":3,"title":["MFS: A Brain-Inspired Memory Formation System for GAN"],"prefix":"10.1109","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2820-0840","authenticated-orcid":false,"given":"Yifan","family":"Chang","sequence":"first","affiliation":[{"name":"Department of Automation, University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3384-7059","authenticated-orcid":false,"given":"Yifan","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Physical Science and Information Technology, Anhui University, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1820-4015","authenticated-orcid":false,"given":"Jian","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha, China"}]},{"given":"Ziyi","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1173-6593","authenticated-orcid":false,"given":"Haifeng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0464-6955","authenticated-orcid":false,"given":"Wenbo","family":"Li","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences, Institute of Intelligent Machines, Hefei, China"}]}],"member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.1016\/s0079-7421(08)60536-8"},{"volume-title":"Generative adversarial network training is a continual learning problem","year":"2018","author":"Liang","key":"ref2"},{"issue":"2","key":"ref3","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1152\/physrev.00032.2012","article-title":"About sleep\u2019s role in memory","volume":"93","author":"Bjorn","year":"2013","journal-title":"Physiol. Rev."},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1038\/nrn2762"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1016\/j.smrv.2005.05.002"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1515\/znc-1998-7-805"},{"doi-asserted-by":"publisher","key":"ref7","DOI":"10.1038\/nn1961"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.1145\/3422622"},{"doi-asserted-by":"publisher","key":"ref9","DOI":"10.1016\/j.neuron.2017.06.011"},{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.1038\/nature08577"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1073\/pnas.1611835114"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1007\/978-3-030-01219-9_9"},{"key":"ref13","first-page":"3987","article-title":"Continual learning through synaptic intelligence","volume-title":"Proc. ICML","author":"Friedemann"},{"key":"ref14","first-page":"13","article-title":"Overcoming catastrophic forgetting for continual learning via model adaptation","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Hu"},{"doi-asserted-by":"publisher","key":"ref15","DOI":"10.1038\/s41583-018-0077-1"},{"doi-asserted-by":"publisher","key":"ref16","DOI":"10.1109\/CVPR.2017.587"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1109\/TNNLS.2021.3072041"},{"volume-title":"Gradient episodic memory for continual learning","year":"2017","author":"David","key":"ref18"},{"volume-title":"SupportNet: Solving catastrophic forgetting in class incremental learning with support data","year":"2018","author":"Li","key":"ref19"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.1016\/j.neuron.2005.02.001"},{"doi-asserted-by":"publisher","key":"ref21","DOI":"10.1523\/JNEUROSCI.19-21-09497.1999"},{"key":"ref22","first-page":"7765","article-title":"Packnet: Adding multiple tasks to a single network by iterative pruning","volume-title":"Proc. CVPR","author":"Arun"},{"volume-title":"Progressive neural networks","year":"2016","author":"Rusu","key":"ref23"},{"doi-asserted-by":"publisher","key":"ref24","DOI":"10.1145\/2647868.2654926"},{"volume-title":"DSD: Dense-sparse-dense training for deep neural networks","year":"2016","author":"Song","key":"ref25"},{"doi-asserted-by":"publisher","key":"ref26","DOI":"10.3156\/jsoft.29.5_177_2"},{"volume-title":"Self-supervised GAN to counter forgetting","year":"2018","author":"Chen","key":"ref27"},{"volume-title":"Continual learning with deep generative replay","year":"2017","author":"Shin","key":"ref28"},{"key":"ref29","first-page":"5962","article-title":"Memory replay GANs: Learning to generate new categories without forgetting","volume-title":"Advances in Neural Information Processing Systems","author":"Wu","year":"2018"},{"doi-asserted-by":"publisher","key":"ref30","DOI":"10.1146\/annurev.psych.55.090902.142050"},{"doi-asserted-by":"publisher","key":"ref31","DOI":"10.1016\/j.tins.2005.06.004"},{"doi-asserted-by":"publisher","key":"ref32","DOI":"10.1007\/bf01931367"},{"volume-title":"Using gradient descent for optimization and learning","year":"2009","author":"Nicolas","key":"ref33"},{"doi-asserted-by":"publisher","key":"ref34","DOI":"10.1016\/0304-3975(85)90224-5"},{"volume-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","year":"2015","author":"Alec","key":"ref35"},{"key":"ref36","first-page":"7354","article-title":"Self-attention generative adversarial networks","volume-title":"Proc. IEEE Conf. ICML","author":"Zhang"},{"doi-asserted-by":"publisher","key":"ref37","DOI":"10.1109\/MSP.2012.2211477"},{"volume-title":"Fashion-MNIST: A novel image dataset for benchmarking machine learning algorithms","year":"2017","author":"Han","key":"ref38"},{"doi-asserted-by":"publisher","key":"ref39","DOI":"10.1109\/TIP.2012.2205006"},{"key":"ref40","first-page":"90","article-title":"On the relationship between feature selection and classification accuracy","volume-title":"Proc. Workshop New Challenges Feature Selection Data Min. Knowl. Discov.","author":"Janecek"},{"volume-title":"GANs trained by a two time-scale update rule converge to a local nash equilibrium","year":"2017","author":"Heusel","key":"ref41"},{"doi-asserted-by":"publisher","key":"ref42","DOI":"10.1016\/j.cviu.2018.10.009"},{"doi-asserted-by":"publisher","key":"ref43","DOI":"10.1109\/ICCV.2017.304"},{"volume-title":"Improved training of Wasserstein GANs","year":"2017","author":"Gulrajani","key":"ref44"},{"doi-asserted-by":"publisher","key":"ref45","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref46","first-page":"1","article-title":"Reading digits in natural images with unsupervised feature learning","volume-title":"Proc. NIPS DLW","author":"Netzer"},{"volume-title":"The CIFAR-10 Dataset","year":"2009","key":"ref47"},{"volume-title":"Learning a probabilistic latent space of object shapes via 3D generative-adversarial modeling","year":"2016","author":"Wu","key":"ref48"},{"key":"ref49","first-page":"3","article-title":"Rectifier nonlinearities improve neural network acoustic models","volume-title":"Proc. ICML","author":"Maas"},{"doi-asserted-by":"publisher","key":"ref50","DOI":"10.1038\/s41593-021-00821-9"},{"doi-asserted-by":"publisher","key":"ref51","DOI":"10.1007\/BF00337259"}],"container-title":["IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/43\/9832686\/09524745.pdf?arnumber=9524745","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T23:21:39Z","timestamp":1705015299000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9524745\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8]]},"references-count":51,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tcad.2021.3108706","relation":{},"ISSN":["0278-0070","1937-4151"],"issn-type":[{"type":"print","value":"0278-0070"},{"type":"electronic","value":"1937-4151"}],"subject":[],"published":{"date-parts":[[2022,8]]}}}