{"id":"https://openalex.org/W4385484522","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191484","title":"A Spiking Neural Network Learning Markov Chain","display_name":"A Spiking Neural Network Learning Markov Chain","publication_year":2023,"publication_date":"2023-06-18","ids":{"openalex":"https://openalex.org/W4385484522","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191484"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn54540.2023.10191484","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn54540.2023.10191484","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","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/A5031421685","display_name":"Mikhail Kiselev","orcid":"https://orcid.org/0000-0001-7403-6418"},"institutions":[{"id":"https://openalex.org/I181171540","display_name":"Chuvash State University","ror":"https://ror.org/01jmd7f74","country_code":"RU","type":"education","lineage":["https://openalex.org/I181171540"]}],"countries":["RU"],"is_corresponding":true,"raw_author_name":"Mikhail Kiselev","raw_affiliation_strings":["Kaspersky,Technology Research Department,Moscow,Russia","Technology Research Department, Kaspersky, Moscow, Russia","Laboratory of Neuromorphic Computations, Chuvash State University, Cheboxary, Russia"],"affiliations":[{"raw_affiliation_string":"Kaspersky,Technology Research Department,Moscow,Russia","institution_ids":[]},{"raw_affiliation_string":"Technology Research Department, Kaspersky, Moscow, Russia","institution_ids":[]},{"raw_affiliation_string":"Laboratory of Neuromorphic Computations, Chuvash State University, Cheboxary, Russia","institution_ids":["https://openalex.org/I181171540"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068821768","display_name":"Alexander Ivanitsky","orcid":null},"institutions":[{"id":"https://openalex.org/I181171540","display_name":"Chuvash State University","ror":"https://ror.org/01jmd7f74","country_code":"RU","type":"education","lineage":["https://openalex.org/I181171540"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Alexander Ivanitsky","raw_affiliation_strings":["Chuvash State University,Department of Physics, Applied Mathematics &#x0026;IT,Cheboxary,Russia"],"affiliations":[{"raw_affiliation_string":"Chuvash State University,Department of Physics, Applied Mathematics &#x0026;IT,Cheboxary,Russia","institution_ids":["https://openalex.org/I181171540"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003753084","display_name":"Andrey Lavrentyev","orcid":"https://orcid.org/0000-0002-9069-483X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Andrey Lavrentyev","raw_affiliation_strings":["Kaspersky,Technology Research Department,Moscow,Russia","Technology Research Department, Kaspersky, Moscow, Russia"],"affiliations":[{"raw_affiliation_string":"Kaspersky,Technology Research Department,Moscow,Russia","institution_ids":[]},{"raw_affiliation_string":"Technology Research Department, Kaspersky, Moscow, Russia","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5031421685"],"corresponding_institution_ids":["https://openalex.org/I181171540"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07624095,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9987999796867371,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.8039087653160095},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.74470454454422},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5921583771705627},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.5602751970291138},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49109601974487305},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.484292209148407},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47297990322113037},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4342972934246063},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28084051609039307},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12656795978546143}],"concepts":[{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.8039087653160095},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.74470454454422},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5921583771705627},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.5602751970291138},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49109601974487305},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.484292209148407},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47297990322113037},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4342972934246063},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28084051609039307},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12656795978546143},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn54540.2023.10191484","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn54540.2023.10191484","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W1975372282","https://openalex.org/W2027443147","https://openalex.org/W2126404188","https://openalex.org/W2137383364","https://openalex.org/W2138913040","https://openalex.org/W2165639766","https://openalex.org/W2255822949","https://openalex.org/W2283674326","https://openalex.org/W2432549741","https://openalex.org/W2549083315","https://openalex.org/W2730274928","https://openalex.org/W2735207540","https://openalex.org/W2765287321","https://openalex.org/W2783525259","https://openalex.org/W2951742412","https://openalex.org/W2964278142","https://openalex.org/W2978572306","https://openalex.org/W2997168740","https://openalex.org/W3011313139","https://openalex.org/W3039836699","https://openalex.org/W3103193585","https://openalex.org/W3110964655","https://openalex.org/W3134038167","https://openalex.org/W4235646468","https://openalex.org/W4293196420","https://openalex.org/W4299785512","https://openalex.org/W6649113185","https://openalex.org/W6680351714","https://openalex.org/W6744537874"],"related_works":["https://openalex.org/W4306904969","https://openalex.org/W4388311650","https://openalex.org/W5922282","https://openalex.org/W1974056099","https://openalex.org/W4245343541","https://openalex.org/W2379651310","https://openalex.org/W2113019827","https://openalex.org/W1541249122","https://openalex.org/W2413828414","https://openalex.org/W2367222340"],"abstract_inverted_index":{"In":[0,46],"this":[1,74,107,131],"paper,":[2],"the":[3,33,47,70,83,88,94,136],"question":[4,26],"how":[5,106,130],"spiking":[6],"neural":[7],"network":[8,132],"(SNN)":[9],"learns":[10],"and":[11,43,100,120,149,159],"fixes":[12],"in":[13,40,82,93,135],"its":[14,152],"internal":[15],"structures":[16],"a":[17,55,59,116,142,146,155],"model":[18],"of":[19,32,90],"external":[20],"world":[21,52,140],"dynamics":[22,53],"is":[23,27,101,104],"explored.":[24],"This":[25],"important":[28],"for":[29],"SNN":[30,114],"implementation":[31],"model-based":[34],"reinforcement":[35],"learning":[36],"(RL),":[37],"finding":[38],"anomalies":[39],"time":[41],"series":[42],"other":[44],"problems.":[45],"present":[48],"work,":[49],"we":[50,79,128],"formalize":[51],"as":[54],"Markov":[56,95],"chain":[57,96],"with":[58,115,154],"priori":[60],"unknown":[61],"state":[62,92],"transition":[63],"probabilities,":[64],"which":[65],"should":[66],"be":[67,98,110],"learnt":[68],"by":[69,112],"network.":[71],"To":[72],"make":[73],"problem":[75],"formulation":[76],"more":[77],"realistic,":[78],"solve":[80],"it":[81],"continuous":[84],"time,":[85],"so":[86],"that":[87],"duration":[89],"every":[91],"may":[97],"different":[99],"unknown.":[102],"It":[103],"demonstrated":[105],"task":[108],"can":[109],"accomplished":[111],"an":[113,126],"specially":[117],"designed":[118],"structure":[119],"local":[121],"synaptic":[122],"plasticity":[123],"rules.":[124],"As":[125],"example,":[127],"show":[129],"motif":[133],"works":[134],"simple":[137],"but":[138],"non-trivial":[139],"where":[141],"ball":[143],"moves":[144],"inside":[145],"square":[147],"box":[148],"bounces":[150],"from":[151],"walls":[153],"random":[156],"new":[157],"direction":[158],"velocity.":[160]},"counts_by_year":[],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}
