{"id":"https://openalex.org/W4390508374","doi":"https://doi.org/10.1186/s13634-023-01092-1","title":"An experimental study of neural estimators of the mutual information between random vectors modeling power spectrum features","display_name":"An experimental study of neural estimators of the mutual information between random vectors modeling power spectrum features","publication_year":2024,"publication_date":"2024-01-02","ids":{"openalex":"https://openalex.org/W4390508374","doi":"https://doi.org/10.1186/s13634-023-01092-1"},"language":"en","primary_location":{"id":"doi:10.1186/s13634-023-01092-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-023-01092-1","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-023-01092-1","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-023-01092-1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013786579","display_name":"Dong-Hoon Shin","orcid":"https://orcid.org/0000-0001-9689-7841"},"institutions":[{"id":"https://openalex.org/I2801036362","display_name":"Agency for Defense Development","ror":"https://ror.org/05fhe0r85","country_code":"KR","type":"government","lineage":["https://openalex.org/I1327899338","https://openalex.org/I1344042128","https://openalex.org/I2801036362","https://openalex.org/I2801339556"]},{"id":"https://openalex.org/I4921948","display_name":"Pusan National University","ror":"https://ror.org/01an57a31","country_code":"KR","type":"education","lineage":["https://openalex.org/I4921948"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Donghoon Shin","raw_affiliation_strings":["Department of Electronics Engineering, Pusan Natoinal University, Busan, South Korea","Maritime Technology Research Institute, Agency for Defense Development, Changwon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, Pusan Natoinal University, Busan, South Korea","institution_ids":["https://openalex.org/I4921948"]},{"raw_affiliation_string":"Maritime Technology Research Institute, Agency for Defense Development, Changwon, South Korea","institution_ids":["https://openalex.org/I2801036362"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073733529","display_name":"Hyung Soon Kim","orcid":"https://orcid.org/0000-0001-5070-897X"},"institutions":[{"id":"https://openalex.org/I4921948","display_name":"Pusan National University","ror":"https://ror.org/01an57a31","country_code":"KR","type":"education","lineage":["https://openalex.org/I4921948"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyung Soon Kim","raw_affiliation_strings":["Department of Electronics Engineering, Pusan Natoinal University, Busan, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-5070-897X","affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, Pusan Natoinal University, Busan, South Korea","institution_ids":["https://openalex.org/I4921948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5073733529"],"corresponding_institution_ids":["https://openalex.org/I4921948"],"apc_list":{"value":1140,"currency":"GBP","value_usd":1398},"apc_paid":{"value":1140,"currency":"GBP","value_usd":1398},"fwci":0.602,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.70231846,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"2024","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9991000294685364,"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/T10320","display_name":"Neural Networks and Applications","score":0.9991000294685364,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/estimator","display_name":"Estimator","score":0.852229118347168},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7087268829345703},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.6768479347229004},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6451172828674316},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5699880123138428},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5120373368263245},{"id":"https://openalex.org/keywords/spectral-density","display_name":"Spectral density","score":0.48867228627204895},{"id":"https://openalex.org/keywords/statistical-power","display_name":"Statistical power","score":0.4779531955718994},{"id":"https://openalex.org/keywords/information-theory","display_name":"Information theory","score":0.4772734045982361},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.45871996879577637},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.42938193678855896},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4213795065879822},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.41209688782691956},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39152657985687256},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32925987243652344},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1961904764175415},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16922295093536377}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.852229118347168},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7087268829345703},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.6768479347229004},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6451172828674316},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5699880123138428},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5120373368263245},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.48867228627204895},{"id":"https://openalex.org/C96608239","wikidata":"https://www.wikidata.org/wiki/Q1199823","display_name":"Statistical power","level":2,"score":0.4779531955718994},{"id":"https://openalex.org/C52622258","wikidata":"https://www.wikidata.org/wiki/Q131222","display_name":"Information theory","level":2,"score":0.4772734045982361},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.45871996879577637},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.42938193678855896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4213795065879822},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.41209688782691956},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39152657985687256},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32925987243652344},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1961904764175415},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16922295093536377},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s13634-023-01092-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-023-01092-1","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-023-01092-1","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:49574e29cc2f47a88666e9fd48b65058","is_oa":true,"landing_page_url":"https://doaj.org/article/49574e29cc2f47a88666e9fd48b65058","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EURASIP Journal on Advances in Signal Processing, Vol 2024, Iss 1, Pp 1-14 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s13634-023-01092-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-023-01092-1","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-023-01092-1","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.41999998688697815,"display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321284","display_name":"Pusan National University","ror":"https://ror.org/01an57a31"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390508374.pdf"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1877570817","https://openalex.org/W1989387577","https://openalex.org/W2014365762","https://openalex.org/W2034593061","https://openalex.org/W2036097867","https://openalex.org/W2044442377","https://openalex.org/W2088214068","https://openalex.org/W2092939357","https://openalex.org/W2096192494","https://openalex.org/W2106809303","https://openalex.org/W2108384452","https://openalex.org/W2116472966","https://openalex.org/W2122925692","https://openalex.org/W2123806929","https://openalex.org/W2130476329","https://openalex.org/W2136922672","https://openalex.org/W2147299274","https://openalex.org/W2166944917","https://openalex.org/W2626799581","https://openalex.org/W4206566734","https://openalex.org/W4230610536","https://openalex.org/W4388297464","https://openalex.org/W6600178739","https://openalex.org/W6636483828"],"related_works":["https://openalex.org/W3124771927","https://openalex.org/W3212925274","https://openalex.org/W4225940264","https://openalex.org/W2750125254","https://openalex.org/W2057609120","https://openalex.org/W2889544313","https://openalex.org/W2111510771","https://openalex.org/W986037092","https://openalex.org/W2392704982","https://openalex.org/W4313429060"],"abstract_inverted_index":{"Abstract":[0],"Mutual":[1],"information":[2],"(MI)":[3],"quantifies":[4],"the":[5,32,40,108,120],"statistical":[6],"dependency":[7],"between":[8,62,125],"a":[9,16,37,51,116],"pair":[10],"of":[11,34,43,55,60,74,94,111,122],"random":[12,63],"variables":[13],"and":[14,22,84],"plays":[15],"central":[17],"role":[18],"in":[19,27,97,115],"signal":[20],"processing":[21,82],"data":[23,81],"analysis.":[24],"Recent":[25],"advances":[26],"machine":[28],"learning":[29],"have":[30],"enabled":[31],"estimation":[33],"MI":[35,61,95,124],"from":[36],"dataset":[38],"using":[39],"expressive":[41],"power":[42,67,75,126],"neural":[44,58,92,113],"networks.":[45],"In":[46,103],"this":[47,98],"study,":[48],"we":[49,106],"conducted":[50],"comparative":[52],"experimental":[53],"analysis":[54],"several":[56],"existing":[57,112],"estimators":[59,114],"vectors":[64],"that":[65,90],"model":[66],"spectrum":[68,76,127],"features.":[69,128],"We":[70],"explored":[71],"alternative":[72],"models":[73],"features":[77],"by":[78],"leveraging":[79],"information-theoretic":[80],"inequality":[83],"bijective":[85],"transformations.":[86],"Empirical":[87],"results":[88],"demonstrated":[89],"each":[91],"estimator":[93],"covered":[96],"study":[99],"has":[100],"its":[101],"limitations.":[102],"practical":[104],"applications,":[105],"recommend":[107],"collective":[109],"use":[110],"complementary":[117],"manner":[118],"for":[119],"problem":[121],"estimating":[123]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-17T06:14:20.161405","created_date":"2025-10-10T00:00:00"}
