{"id":"https://openalex.org/W4312814879","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892805","title":"Proposal of Reconstructive Reservoir Computing to Detect Anomaly in Time-series Signals","display_name":"Proposal of Reconstructive Reservoir Computing to Detect Anomaly in Time-series Signals","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312814879","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892805"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892805","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892805","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088557334","display_name":"Junya Kato","orcid":"https://orcid.org/0000-0001-5432-157X"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Junya Kato","raw_affiliation_strings":["The University of Tokyo,Dept. of EE & IS,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Dept. of EE & IS,Tokyo,Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025420478","display_name":"Gouhei Tanaka","orcid":"https://orcid.org/0000-0002-6223-4406"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Gouhei Tanaka","raw_affiliation_strings":["IRCN, The University of Tokyo,Tokyo,Japan","IRCN, The University of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IRCN, The University of Tokyo,Tokyo,Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"IRCN, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085544355","display_name":"Ryosho Nakane","orcid":"https://orcid.org/0000-0002-9059-9349"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryosho Nakane","raw_affiliation_strings":["The University of Tokyo,Dept. of EE & IS,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Dept. of EE & IS,Tokyo,Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075783559","display_name":"Akira Hirose","orcid":"https://orcid.org/0000-0002-6936-9733"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akira Hirose","raw_affiliation_strings":["The University of Tokyo,Dept. of EE & IS,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Dept. of EE & IS,Tokyo,Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9818000197410583,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11513","display_name":"stochastic dynamics and bifurcation","score":0.9814000129699707,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.85068279504776},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.77765953540802},{"id":"https://openalex.org/keywords/reservoir-computing","display_name":"Reservoir computing","score":0.7411146759986877},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.727260410785675},{"id":"https://openalex.org/keywords/echo-state-network","display_name":"Echo state network","score":0.6310862302780151},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5934231281280518},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5763798952102661},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5458226799964905},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4865207076072693},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40263134241104126},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37652865052223206},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3642151355743408},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.31546550989151},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2981105148792267},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2123420536518097},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06434577703475952}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.85068279504776},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.77765953540802},{"id":"https://openalex.org/C135796866","wikidata":"https://www.wikidata.org/wiki/Q7315328","display_name":"Reservoir computing","level":4,"score":0.7411146759986877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.727260410785675},{"id":"https://openalex.org/C172025690","wikidata":"https://www.wikidata.org/wiki/Q5332763","display_name":"Echo state network","level":4,"score":0.6310862302780151},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5934231281280518},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5763798952102661},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5458226799964905},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4865207076072693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40263134241104126},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37652865052223206},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3642151355743408},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.31546550989151},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2981105148792267},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2123420536518097},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06434577703475952},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892805","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892805","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.9100000262260437,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G2280667928","display_name":null,"funder_award_id":"JPNP16007","funder_id":"https://openalex.org/F4320321034","funder_display_name":"New Energy and Industrial Technology Development Organization"}],"funders":[{"id":"https://openalex.org/F4320321034","display_name":"New Energy and Industrial Technology Development Organization","ror":"https://ror.org/0055k7a87"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1876967670","https://openalex.org/W2103179919","https://openalex.org/W2113132555","https://openalex.org/W2119002676","https://openalex.org/W2127979711","https://openalex.org/W2204904589","https://openalex.org/W2288218992","https://openalex.org/W2552475543","https://openalex.org/W2574572704","https://openalex.org/W2601590138","https://openalex.org/W2756489700","https://openalex.org/W2765355882","https://openalex.org/W2789326804","https://openalex.org/W2794103404","https://openalex.org/W2887258823","https://openalex.org/W2892542319","https://openalex.org/W2921125227","https://openalex.org/W2942245950","https://openalex.org/W2942682738","https://openalex.org/W2965981069","https://openalex.org/W2972520844","https://openalex.org/W2982294822","https://openalex.org/W3011304975","https://openalex.org/W3022832625","https://openalex.org/W3112003035","https://openalex.org/W3153740699","https://openalex.org/W3161223230","https://openalex.org/W3200514678","https://openalex.org/W6756546600","https://openalex.org/W6767617565"],"related_works":["https://openalex.org/W57315087","https://openalex.org/W2010974764","https://openalex.org/W4386848428","https://openalex.org/W1996014987","https://openalex.org/W4205631599","https://openalex.org/W2021379535","https://openalex.org/W2903992663","https://openalex.org/W4237814686","https://openalex.org/W2997427060","https://openalex.org/W2953065922"],"abstract_inverted_index":{"In":[0,15,137],"this":[1],"paper,":[2],"we":[3,68,104],"propose":[4],"reconstructive":[5],"reservoir":[6,139,155,165],"computing":[7,140,156,166],"(RRC)":[8],"to":[9,24,30,37],"detect":[10,43],"anomaly":[11,44,65,75,86,98,135],"in":[12,94,114,198],"time-series":[13,61,102],"signals.":[14],"the":[16,54,82,108,132,159,199],"RRC,":[17],"an":[18,58,112,191],"echo":[19],"state":[20],"network":[21],"(ESN)":[22],"learns":[23],"reconstruct":[25,38],"normal":[26,119],"input":[27,32],"signals":[28,62],"fed":[29],"its":[31,47,115],"terminals.":[33],"Since":[34],"it":[35,72],"fails":[36],"abnormal":[39,121],"signals,":[40,103],"RRC":[41,83,188],"can":[42,73,152],"based":[45],"on":[46],"reconstruction":[48,109],"error.":[49],"It":[50],"is":[51,167],"shown":[52],"for":[53,64,85,97,101,170],"first":[55],"time":[56],"that":[57,71,81,107,126],"ESN":[59],"reconstructs":[60],"effectively":[63],"detection":[66,76,87,99,186],"while":[67],"already":[69],"know":[70],"realize":[74],"by":[77,187],"forecasting.":[78],"Experiments":[79],"demonstrate":[80],"works":[84],"effectively.":[88],"Though":[89],"forecasting":[90],"errors":[91],"are":[92],"used":[93],"conventional":[95],"methods":[96],"working":[100],"find":[105,125],"experimentally":[106],"method":[110],"has":[111,141],"advantage":[113],"larger":[116],"margin":[117],"between":[118],"and":[120],"errors.":[122],"We":[123,151],"also":[124,153],"a":[127],"smaller":[128],"leaking":[129],"rate":[130],"enhances":[131],"ability":[133],"of":[134,143,161,178,194],"detection.":[136],"general,":[138],"merits":[142],"fast":[144],"training":[145],"and,":[146],"consequently,":[147],"less":[148],"energy":[149],"consumption.":[150],"make":[154],"work":[157],"with":[158],"use":[160],"physical":[162],"phenomena.":[163],"Utilizing":[164],"really":[168],"meaningful":[169],"these":[171],"aspects":[172],"which":[173],"layered":[174],"or":[175],"other":[176],"types":[177],"recurrent":[179],"neural":[180],"networks":[181],"do":[182],"not":[183],"have.":[184],"Anomaly":[185],"will":[189],"be":[190],"important":[192],"application":[193],"micro":[195],"physical-reservoir":[196],"devices":[197],"near":[200],"future.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}