{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T06:14:54Z","timestamp":1744179294145,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031232091"},{"type":"electronic","value":"9783031232107"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-23210-7_10","type":"book-chapter","created":{"date-parts":[[2023,2,21]],"date-time":"2023-02-21T21:26:58Z","timestamp":1677014818000},"page":"105-114","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Recurrent Neural Networks as\u00a0Electrical Networks, a\u00a0Formalization"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7455-1193","authenticated-orcid":false,"given":"Mariano","family":"Caruso","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3917-920X","authenticated-orcid":false,"given":"Cecilia","family":"Jarne","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,2,22]]},"reference":[{"issue":"5","key":"10_CR1","doi-asserted-by":"publisher","first-page":"1029","DOI":"10.1007\/s00034-010-9261-x","volume":"30","author":"MS Ansari","year":"2011","unstructured":"Ansari, M.S., Rahman, S.A.: DVCC-based non-linear feedback neural circuit for solving system of linear equations. Circ. Syst. Sig. Process. 30(5), 1029\u20131045 (2011)","journal-title":"Circ. Syst. Sig. Process."},{"key":"10_CR2","unstructured":"Balabanian, N., Bickart, T.A.: Linear Network Theory: Analysis, Properties. Design and Synthesis. Weber Systems (1982)"},{"key":"10_CR3","unstructured":"Carlin, H., et al.: Network Theory: An Introduction to Reciprocal and Nonreciprocal Circuits. Prentice-Hall Series in Electrical Engineering. Prentice-Hall (1964)"},{"key":"10_CR4","doi-asserted-by":"crossref","unstructured":"Duncker, L., Sahani, M.: Dynamics on the manifold: identifying computational dynamical activity from neural population recordings. Curr. Opin. Neurobiol. 70, 163\u2013170 (2021)","DOI":"10.1016\/j.conb.2021.10.014"},{"issue":"3","key":"10_CR5","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1016\/0893-6080(89)90003-8","volume":"2","author":"K Funahashi","year":"1989","unstructured":"Funahashi, K.: On the approximate realization of continuous mappings by neural networks. Neural Networks 2(3), 183\u2013192 (1989)","journal-title":"Neural Networks"},{"issue":"6","key":"10_CR6","doi-asserted-by":"publisher","first-page":"801","DOI":"10.1016\/S0893-6080(05)80125-X","volume":"6","author":"K Funahashi","year":"1993","unstructured":"Funahashi, K., Nakamura, Y.: Approximation of dynamical systems by continuous time recurrent neural networks. Neural Networks 6(6), 801\u2013806 (1993)","journal-title":"Neural Networks"},{"issue":"6103","key":"10_CR7","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1126\/science.1227356","volume":"338","author":"W Gerstner","year":"2012","unstructured":"Gerstner, W., Sprekeler, H., Deco, G.: Theory and simulation in neuroscience. Science 338(6103), 60\u201365 (2012)","journal-title":"Science"},{"issue":"10","key":"10_CR8","doi-asserted-by":"publisher","first-page":"3088","DOI":"10.1073\/pnas.81.10.3088","volume":"81","author":"JJ Hopfield","year":"1984","unstructured":"Hopfield, J.J.: Neurons with graded response have collective computational properties like those of two-state neurons. Proc. Natl. Acad. Sci. 81(10), 3088\u20133092 (1984)","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"9","key":"10_CR9","doi-asserted-by":"publisher","first-page":"1531","DOI":"10.1016\/0893-6080(95)00129-8","volume":"9","author":"N Kurita","year":"1996","unstructured":"Kurita, N., Funahashi, K.: On the Hopfield neural networks and mean field theory. Neural Networks 9(9), 1531\u20131540 (1996)","journal-title":"Neural Networks"},{"issue":"10","key":"10_CR10","doi-asserted-by":"publisher","first-page":"1629","DOI":"10.1109\/5.58356","volume":"78","author":"C Mead","year":"1990","unstructured":"Mead, C.: Neuromorphic electronic systems. Proc. IEEE 78(10), 1629\u20131636 (1990)","journal-title":"Proc. IEEE"},{"key":"10_CR11","doi-asserted-by":"crossref","unstructured":"Monroe, D.: Neuromorphic computing gets ready for the (really) big time. Commun. ACM 57(6), 13\u201315 (2014)","DOI":"10.1145\/2601069"},{"key":"10_CR12","doi-asserted-by":"crossref","unstructured":"Sch\u00e4fer, A.M., et al.: Recurrent neural networks are universal approximators. In: Artificial Neural Networks\u2014ICANN 2006, pp. 632\u2013640. Springer, Berlin (2006)","DOI":"10.1007\/11840817_66"},{"key":"10_CR13","doi-asserted-by":"crossref","unstructured":"Siegelmann, H.T., et al.: On the computational power of neural nets. In: Proceedings of the Fifth Annual Workshop on Computational Learning Theory, COLT\u201992, pp. 440\u2013449. Association for Computing Machinery, New York, NY, USA (1992)","DOI":"10.1145\/130385.130432"},{"key":"10_CR14","doi-asserted-by":"crossref","unstructured":"Sussillo, D.: Neural circuits as computational dynamical systems. Curr. Opin. Neurobiol. 25, 156\u2013163 (2014)","DOI":"10.1016\/j.conb.2014.01.008"},{"issue":"3","key":"10_CR15","doi-asserted-by":"publisher","first-page":"626","DOI":"10.1162\/NECO_a_00409","volume":"25","author":"D Sussillo","year":"2013","unstructured":"Sussillo, D., Barak, O.: Opening the black box: low-dimensional dynamics in high-dimensional recurrent neural networks. Neural Comput. 25(3), 626\u2013649 (2013)","journal-title":"Neural Comput."},{"issue":"7","key":"10_CR16","doi-asserted-by":"publisher","first-page":"3424","DOI":"10.1007\/s00034-019-01324-6","volume":"39","author":"Z Tabekoueng Njitacke","year":"2020","unstructured":"Tabekoueng Njitacke, Z., Kengne, J., Fotsin, H.B.: Coexistence of multiple stable states and bursting oscillations in a 4d Hopfield neural network. Circ. Syst. Sig. Process. 39(7), 3424\u20133444 (2020)","journal-title":"Circ. Syst. Sig. Process."},{"key":"10_CR17","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1016\/j.neunet.2016.04.001","volume":"80","author":"AP Trischler","year":"2016","unstructured":"Trischler, A.P., D\u2019Eleuterio, G.M.: Synthesis of recurrent neural networks for dynamical system simulation. Neural Networks 80, 67\u201378 (2016)","journal-title":"Neural Networks"}],"container-title":["Lecture Notes in Networks and Systems","Distributed Computing and Artificial Intelligence, Special Sessions, 19th International Conference"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-23210-7_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,29]],"date-time":"2024-01-29T08:03:22Z","timestamp":1706515402000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-23210-7_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031232091","9783031232107"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-23210-7_10","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"22 February 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Distributed Computing and Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"L\u00b4Aquila","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 July 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 July 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dcai2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.dcai-conference.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}