{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T15:12:05Z","timestamp":1777302725855,"version":"3.51.4"},"reference-count":34,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/OAPA.html"}],"funder":[{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People's Republic of China","doi-asserted-by":"publisher","award":["2015CB358700"],"award-info":[{"award-number":["2015CB358700"]}],"id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772059"],"award-info":[{"award-number":["61772059"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61421003"],"award-info":[{"award-number":["61421003"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Beijing Advanced Innovation Center for Big Data and Brain Computing"},{"DOI":"10.13039\/501100011347","name":"State Key Laboratory of Software Development Environment","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100011347","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2018.2890297","type":"journal-article","created":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T19:48:17Z","timestamp":1546372097000},"page":"12511-12520","source":"Crossref","is-referenced-by-count":10,"title":["Recurrent Neural Networks With Finite Memory Length"],"prefix":"10.1109","volume":"7","author":[{"given":"Dingkun","family":"Long","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1207-0300","authenticated-orcid":false,"given":"Richong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongyi","family":"Mao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","author":"inan","year":"2016","journal-title":"Tying word vectors and word classifiers A loss framework for language modeling"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/E17-2025"},{"key":"ref31","author":"krause","year":"2017","journal-title":"Dynamic evaluation of neural sequence models"},{"key":"ref30","first-page":"1","article-title":"Improving neural language models with a continuous cache","author":"grave","year":"2017","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref34","first-page":"4189","article-title":"Recurrent highway networks","author":"zilly","year":"2017","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref10","first-page":"125","article-title":"WaveNet: A generative model for raw audio","author":"van den oord","year":"2016","journal-title":"Proc ISCA Speech Synth Workshop"},{"key":"ref11","first-page":"1243","article-title":"Convolutional sequence to sequence learning","author":"gehring","year":"2017","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref12","article-title":"Short term memory in echo state networks","author":"jaeger","year":"2002"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0804451105"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2677968"},{"key":"ref15","first-page":"7995","article-title":"Regularizing RNNs for caption generation by reconstructing the past with the present","author":"chen","year":"2018","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref16","first-page":"4797","article-title":"Conditional image generation with PixelCNN decoders","author":"van den oord","year":"2016","journal-title":"Proc NIPS"},{"key":"ref17","first-page":"40","author":"von bertalanffy","year":"1968","journal-title":"General system theory"},{"key":"ref18","first-page":"4790","article-title":"Conditional image generation with PixelCNN decoders","author":"van den oord","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref19","author":"bahdanau","year":"2014","journal-title":"Neural machine translation by jointly learning to align and translate"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2010-343"},{"key":"ref4","first-page":"173","article-title":"Deep speech 2: End-to-end speech recognition in English and Mandarin","author":"amodei","year":"2016","journal-title":"Proc 33th Int Conf Mach Learn (ICML)"},{"key":"ref27","author":"zaremba","year":"2014","journal-title":"Recurrent Neural Network Regularization"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1179"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2793911"},{"key":"ref29","author":"merity","year":"2016","journal-title":"Pointer sentinel mixture models"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D15-1167"},{"key":"ref8","first-page":"1310","article-title":"On the difficulty of training recurrent neural networks","volume":"28","author":"pascanu","year":"2013","journal-title":"Proc ICML"},{"key":"ref7","first-page":"873","article-title":"Dynamical isometry and a mean field theory of RNNs: Gating enables signal propagation in recurrent neural networks","author":"chen","year":"2018","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref9","first-page":"933","article-title":"Language modeling with gated convolutional networks","author":"dauphin","year":"2017","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/0364-0213(90)90002-E"},{"key":"ref20","first-page":"4898","article-title":"Understanding the effective receptive field in deep convolutional neural networks","author":"luo","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref22","author":"kingma","year":"2014","journal-title":"Adam A method for stochastic optimization"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref24","first-page":"142","article-title":"Learning word vectors for sentiment analysis","author":"maas","year":"2011","journal-title":"Proc Ann Meeting on Assoc for Computational Linguistics (ACL)"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/72.279181"},{"key":"ref26","author":"longpre","year":"2016","journal-title":"A way out of the odyssey Analyzing and combining recent insights for LSTMs"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.3115\/1072228.1072378"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08598932.pdf?arnumber=8598932","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T23:51:00Z","timestamp":1643241060000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8598932\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/access.2018.2890297","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]}}}