{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T14:07:20Z","timestamp":1773842840280,"version":"3.50.1"},"reference-count":20,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,12,5]],"date-time":"2021-12-05T00:00:00Z","timestamp":1638662400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,5]],"date-time":"2021-12-05T00:00:00Z","timestamp":1638662400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,5]]},"DOI":"10.1109\/dac18074.2021.9586133","type":"proceedings-article","created":{"date-parts":[[2021,11,8]],"date-time":"2021-11-08T23:30:34Z","timestamp":1636414234000},"page":"361-366","source":"Crossref","is-referenced-by-count":16,"title":["Neuromorphic Algorithm-hardware Codesign for Temporal Pattern Learning"],"prefix":"10.1109","author":[{"given":"Haowen","family":"Fang","sequence":"first","affiliation":[{"name":"Syracuse University,Department of Electrical Engineering and Computer Science,Syracuse,NY"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Brady","family":"Taylor","sequence":"additional","affiliation":[{"name":"Duke University,Department of Electrical and Computer Engineering,Durham,NC"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziru","family":"Li","sequence":"additional","affiliation":[{"name":"Duke University,Department of Electrical and Computer Engineering,Durham,NC"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zaidao","family":"Mei","sequence":"additional","affiliation":[{"name":"Syracuse University,Department of Electrical Engineering and Computer Science,Syracuse,NY"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hai Helen","family":"Li","sequence":"additional","affiliation":[{"name":"Duke University,Department of Electrical and Computer Engineering,Durham,NC"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qinru","family":"Qiu","sequence":"additional","affiliation":[{"name":"Syracuse University,Department of Electrical Engineering and Computer Science,Syracuse,NY"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2019.2931595"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ISCAS.2016.7539039"},{"key":"ref12","first-page":"3882","article-title":"Phased lstm: Accelerating recurrent network training for long or event-based sequences","author":"neil","year":"2016","journal-title":"In Advances in Neural Information Processing Systems"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2013.2251072"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2017.7966125"},{"key":"ref15","article-title":"Deep convolutional spiking neural networks for image classification","author":"vaila","year":"2019","journal-title":"arXiv preprint arXiv 1903 11593"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/2742060.2743756"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1038\/nnano.2012.240"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3407197.3407225"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1162\/neco_a_01086"},{"key":"ref4","author":"eliasmith","year":"2004","journal-title":"Neural Engineering Computation Representation and Dynamics in Neurobiological Systems"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3044364"},{"key":"ref6","article-title":"Is neuromorphic mnist neuromorphic? analyzing the discriminative power of neuromorphic datasets in the time domain","author":"iyer","year":"2018","journal-title":"arXiv preprint arXiv 1807 01013"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781107447615"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/2744769.2744783"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"508","DOI":"10.3389\/fnins.2016.00508","article-title":"Training deep spiking neural networks using backpropagation","volume":"10","author":"lee","year":"2016","journal-title":"Frontiers in Neuroscience"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s10827-007-0038-6"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00058"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ISVLSI.2016.46"},{"key":"ref20","article-title":"The remarkable robustness of surrogate gradient learning for instilling complex function in spiking neural networks","author":"zenke","year":"2020","journal-title":"BioRxiv"}],"event":{"name":"2021 58th ACM\/IEEE Design Automation Conference (DAC)","location":"San Francisco, CA, USA","start":{"date-parts":[[2021,12,5]]},"end":{"date-parts":[[2021,12,9]]}},"container-title":["2021 58th ACM\/IEEE Design Automation Conference (DAC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9585997\/9586083\/09586133.pdf?arnumber=9586133","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T17:44:03Z","timestamp":1717609443000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9586133\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,5]]},"references-count":20,"URL":"https:\/\/doi.org\/10.1109\/dac18074.2021.9586133","relation":{},"subject":[],"published":{"date-parts":[[2021,12,5]]}}}