{"id":"https://openalex.org/W4285324034","doi":"https://doi.org/10.1109/mhs53471.2021.9767178","title":"Physics-informed reservoir computing with autonomously switching readouts: a case study in pneumatic artificial muscles","display_name":"Physics-informed reservoir computing with autonomously switching readouts: a case study in pneumatic artificial muscles","publication_year":2021,"publication_date":"2021-12-05","ids":{"openalex":"https://openalex.org/W4285324034","doi":"https://doi.org/10.1109/mhs53471.2021.9767178"},"language":"en","primary_location":{"id":"doi:10.1109/mhs53471.2021.9767178","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mhs53471.2021.9767178","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Symposium on Micro-NanoMehatronics and Human Science (MHS)","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/A5077650758","display_name":"Wentao Sun","orcid":"https://orcid.org/0000-0002-1016-7424"},"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":"Wentao Sun","raw_affiliation_strings":["Graduate School of Information Science and Technology, The University of Tokyo,Tokyo,Japan,113-8656"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science and Technology, The University of Tokyo,Tokyo,Japan,113-8656","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090119956","display_name":"Nozomi Akashi","orcid":"https://orcid.org/0000-0002-8358-3138"},"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":"Nozomi Akashi","raw_affiliation_strings":["Graduate School of Information Science and Technology, The University of Tokyo,Tokyo,Japan,113-8656"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science and Technology, The University of Tokyo,Tokyo,Japan,113-8656","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010543059","display_name":"Yasuo Kuniyoshi","orcid":"https://orcid.org/0000-0001-8443-4161"},"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":"Yasuo Kuniyoshi","raw_affiliation_strings":["Graduate School of Information Science and Technology, The University of Tokyo,Tokyo,Japan,113-8656"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science and Technology, The University of Tokyo,Tokyo,Japan,113-8656","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065659757","display_name":"Kohei Nakajima","orcid":"https://orcid.org/0000-0001-5589-4054"},"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":"Kohei Nakajima","raw_affiliation_strings":["Graduate School of Information Science and Technology, The University of Tokyo,Tokyo,Japan,113-8656"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science and Technology, The University of Tokyo,Tokyo,Japan,113-8656","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":1.3188,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.84533014,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"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":0.9997000098228455,"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":0.9997000098228455,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9965000152587891,"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"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9679999947547913,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reservoir-computing","display_name":"Reservoir computing","score":0.7897402048110962},{"id":"https://openalex.org/keywords/echo-state-network","display_name":"Echo state network","score":0.6177209615707397},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6084309220314026},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.565902829170227},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5473303198814392},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5254384875297546},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.49843931198120117},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.47080931067466736},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.46521782875061035},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.3913959562778473},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3599393963813782},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.33035409450531006},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.22238481044769287},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19714781641960144}],"concepts":[{"id":"https://openalex.org/C135796866","wikidata":"https://www.wikidata.org/wiki/Q7315328","display_name":"Reservoir computing","level":4,"score":0.7897402048110962},{"id":"https://openalex.org/C172025690","wikidata":"https://www.wikidata.org/wiki/Q5332763","display_name":"Echo state network","level":4,"score":0.6177209615707397},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6084309220314026},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.565902829170227},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5473303198814392},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5254384875297546},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.49843931198120117},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.47080931067466736},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.46521782875061035},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.3913959562778473},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3599393963813782},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.33035409450531006},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.22238481044769287},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19714781641960144},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mhs53471.2021.9767178","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mhs53471.2021.9767178","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Symposium on Micro-NanoMehatronics and Human Science (MHS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1485346879","https://openalex.org/W2043385819","https://openalex.org/W2049292590","https://openalex.org/W2054628872","https://openalex.org/W2070184318","https://openalex.org/W2083886793","https://openalex.org/W2097815751","https://openalex.org/W2136867044","https://openalex.org/W2152928668","https://openalex.org/W2177933918","https://openalex.org/W2899283552","https://openalex.org/W2945889873","https://openalex.org/W3022606092","https://openalex.org/W3035814335","https://openalex.org/W3046414114","https://openalex.org/W3100560308","https://openalex.org/W3107724495","https://openalex.org/W3163993681","https://openalex.org/W3169610371","https://openalex.org/W3214007446","https://openalex.org/W4251181231","https://openalex.org/W6680539541","https://openalex.org/W6682372034"],"related_works":["https://openalex.org/W57315087","https://openalex.org/W2010974764","https://openalex.org/W4386848428","https://openalex.org/W4205631599","https://openalex.org/W2021379535","https://openalex.org/W4205591045","https://openalex.org/W2020067398","https://openalex.org/W2903992663","https://openalex.org/W4237814686","https://openalex.org/W2997427060"],"abstract_inverted_index":{"We":[0,26,97,122],"introduce":[1],"an":[2,28],"approach":[3],"based":[4],"on":[5,58],"physics-informed":[6],"neural":[7,38],"networks":[8],"to":[9,45],"predict":[10],"the":[11,46,51,60,64,86,92,95,101,106,117,120,134,139,146,150],"length":[12,93,118],"of":[13,23,36,50,66,94,105,119,149],"a":[14,21,34,130],"McKibben":[15],"pneumatic":[16],"artificial":[17],"muscle":[18],"(PAM)":[19],"from":[20],"series":[22],"pressure":[24],"measurements.":[25],"implemented":[27],"echo":[29],"state":[30,55,136,148],"network,":[31],"which":[32],"is":[33,63,73],"type":[35],"recurrent":[37,88],"network":[39,89],"with":[40,145],"autonomously":[41,137],"switching":[42,72,109],"readouts":[43,110],"corresponding":[44],"different":[47,102],"physical":[48,54,103,147],"states":[49,80,104],"PAM.":[52,96,121,151],"The":[53,71],"we":[56],"focus":[57],"in":[59,115,141],"current":[61],"study":[62],"direction":[65],"motion":[67],"affected":[68],"by":[69,75,84,108],"hysteresis.":[70],"realized":[74],"introducing":[76],"gate":[77],"architecture,":[78],"whose":[79],"are":[81,143],"also":[82,123],"controlled":[83],"using":[85],"same":[87],"that":[90,99,125],"outputs":[91],"demonstrated":[98,124],"handling":[100],"PAM":[107],"will":[111],"robustly":[112],"yield":[113],"performance":[114],"predicting":[116],"Gaussian":[126],"mixture":[127],"models":[128],"as":[129],"classifier":[131],"for":[132],"clustering":[133],"reservoir":[135],"and":[138],"results":[140],"classification":[142],"consistent":[144]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}