{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T10:20:43Z","timestamp":1763202043314},"reference-count":22,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,5]]},"DOI":"10.1109\/ijcnn.2017.7966138","type":"proceedings-article","created":{"date-parts":[[2017,7,10]],"date-time":"2017-07-10T21:41:30Z","timestamp":1499722890000},"source":"Crossref","is-referenced-by-count":19,"title":["State initialization for recurrent neural network modeling of time-series data"],"prefix":"10.1109","author":[{"given":"Nima","family":"Mohajerin","sequence":"first","affiliation":[]},{"given":"Steven L.","family":"Waslander","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.conengprac.2011.04.005"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2009.5152561"},{"key":"ref12","author":"jaeger","year":"2002","journal-title":"Tutorial on training recurrent neural networks covering BPPT RTRL EKF and the&#x201D; echo state network&#x201D; approach"},{"key":"ref13","author":"kolen","year":"2001","journal-title":"A Field Guide to Dynamical Recurrent Networks"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1987.1057328"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1201\/CRCINTCOMINT"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/SMC.2014.6974106"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/SMC.2015.77"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/72.80202"},{"key":"ref19","author":"pascanu","year":"2014","journal-title":"How to construct deep recurrent neural networks"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00052"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248110"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2011.2134090"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390177"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(05)80125-X"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3182\/20110828-6-IT-1002.02016"},{"key":"ref2","author":"bishop","year":"2006","journal-title":"Pattern Recognition and Machine Learning"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CDC.2013.6759988"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2205597"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1007\/11840817_66","article-title":"Recurrent neural networks are universal approximators","author":"sch\u00e4fer","year":"2006","journal-title":"Artificial Neural Networks&#x2014;ICANN 2006"},{"key":"ref22","author":"vapnik","year":"2013","journal-title":"The Nature of Statistical Learning Theory"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.2514\/6.2012-5049"}],"event":{"name":"2017 International Joint Conference on Neural Networks (IJCNN)","location":"Anchorage, AK, USA","start":{"date-parts":[[2017,5,14]]},"end":{"date-parts":[[2017,5,19]]}},"container-title":["2017 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7958416\/7965814\/07966138.pdf?arnumber=7966138","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,29]],"date-time":"2019-09-29T10:14:05Z","timestamp":1569752045000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7966138\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/ijcnn.2017.7966138","relation":{},"subject":[],"published":{"date-parts":[[2017,5]]}}}