{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T14:55:07Z","timestamp":1777128907107,"version":"3.51.4"},"reference-count":30,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science (JSPS) KAKENHI","doi-asserted-by":"publisher","award":["20K11882"],"award-info":[{"award-number":["20K11882"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Japan Science and Technology Agency (JST)-Mirai Program, Japan","award":["JPMJMI19B1"],"award-info":[{"award-number":["JPMJMI19B1"]}]},{"name":"Japan Science and Technology Agency (JST)-Mirai Program, Japan","award":["Japan"],"award-info":[{"award-number":["Japan"]}]},{"DOI":"10.13039\/501100001863","name":"New Energy and Industrial Technology Development Organization","doi-asserted-by":"publisher","award":["JPNP16007"],"award-info":[{"award-number":["JPNP16007"]}],"id":[{"id":"10.13039\/501100001863","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/access.2022.3158755","type":"journal-article","created":{"date-parts":[[2022,3,10]],"date-time":"2022-03-10T20:25:06Z","timestamp":1646943906000},"page":"28535-28544","source":"Crossref","is-referenced-by-count":26,"title":["Computational Efficiency of Multi-Step Learning Echo State Networks for Nonlinear Time Series Prediction"],"prefix":"10.1109","volume":"10","author":[{"given":"Takanori","family":"Akiyama","sequence":"first","affiliation":[{"name":"Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6223-4406","authenticated-orcid":false,"given":"Gouhei","family":"Tanaka","sequence":"additional","affiliation":[{"name":"Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","article-title":"The \u2018echo state\u2019 approach to analysing and training recurrent neural networks-with an Erratum note","author":"Jaeger","year":"2001"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1126\/science.1091277"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2009.03.005"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.03.005"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2018.08.025"},{"key":"ref6","article-title":"Short term memory in echo state networks","author":"Jaeger","year":"2002"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1063\/1.5028373"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.5194\/npg-27-373-2020"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-35289-8_36"},{"key":"ref10","article-title":"Deep-ESN: A multiple projection-encoding hierarchical reservoir computing framework","author":"Ma","year":"2017","journal-title":"arXiv:1711.05255"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.11.073"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.08.122"},{"key":"ref13","first-page":"2307","article-title":"Phoneme recognition with large hierarchical reservoirs","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Triefenbach"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.12.089"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9206771"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2019.8851876"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-017-10257-6"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.120.024102"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.98.012215"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1002\/widm.1200"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2017.2734043"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1515\/9781400841356.38"},{"issue":"3","key":"ref23","first-page":"501","article-title":"On the solution of ill-posed problems and the method of regularization","volume":"151","author":"Tikhonov","year":"1963","journal-title":"Dokl. Akad. Nauk"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0469(1963)020<0130:dnf>2.0.co;2"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-30493-5_12"},{"key":"ref26","first-page":"609","article-title":"Adaptive nonlinear system identification with echo state networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Jaeger"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2089641"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00374"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CISDA.2015.7208637"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICNN.1993.298828"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9668973\/09732994.pdf?arnumber=9732994","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,17]],"date-time":"2024-01-17T23:12:45Z","timestamp":1705533165000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9732994\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/access.2022.3158755","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}