{"id":"https://openalex.org/W2662097648","doi":"https://doi.org/10.1109/icassp.2017.7953331","title":"Autoencoders trained with relevant information: Blending Shannon and Wiener's perspectives","display_name":"Autoencoders trained with relevant information: Blending Shannon and Wiener's perspectives","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2662097648","doi":"https://doi.org/10.1109/icassp.2017.7953331","mag":"2662097648"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2017.7953331","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2017.7953331","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5041358503","display_name":"Shujian Yu","orcid":"https://orcid.org/0000-0002-6385-1705"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shujian Yu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Florida, FL"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Florida, FL","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025034683","display_name":"Matthew S. Emigh","orcid":"https://orcid.org/0000-0002-1438-6069"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew Emigh","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Florida, FL"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Florida, FL","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003992022","display_name":"Eder Santana","orcid":"https://orcid.org/0000-0003-1261-6382"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eder Santana","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Florida, FL"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Florida, FL","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019504861","display_name":"Jos\u00e9 C. Pr\u0131\u0301ncipe","orcid":"https://orcid.org/0000-0002-3449-3531"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jose C. Principe","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Florida, FL"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Florida, FL","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I33213144"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"6115","last_page":"6119"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.993399977684021,"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":0.993399977684021,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9915000200271606,"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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9794999957084656,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/extrapolation","display_name":"Extrapolation","score":0.6795463562011719},{"id":"https://openalex.org/keywords/wiener-filter","display_name":"Wiener filter","score":0.6685256958007812},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.6678541898727417},{"id":"https://openalex.org/keywords/information-theory","display_name":"Information theory","score":0.6503156423568726},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5897417664527893},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.588361918926239},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5732519626617432},{"id":"https://openalex.org/keywords/noisy-channel-coding-theorem","display_name":"Noisy-channel coding theorem","score":0.5706573128700256},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5038029551506042},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.4715053141117096},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.46185624599456787},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4150194823741913},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34200990200042725},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2998608648777008},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2966636121273041},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19458219408988953},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.17233923077583313},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08729991316795349}],"concepts":[{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.6795463562011719},{"id":"https://openalex.org/C18537770","wikidata":"https://www.wikidata.org/wiki/Q25523","display_name":"Wiener filter","level":2,"score":0.6685256958007812},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.6678541898727417},{"id":"https://openalex.org/C52622258","wikidata":"https://www.wikidata.org/wiki/Q131222","display_name":"Information theory","level":2,"score":0.6503156423568726},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5897417664527893},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.588361918926239},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5732519626617432},{"id":"https://openalex.org/C103073706","wikidata":"https://www.wikidata.org/wiki/Q2345282","display_name":"Noisy-channel coding theorem","level":5,"score":0.5706573128700256},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5038029551506042},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.4715053141117096},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.46185624599456787},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4150194823741913},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34200990200042725},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2998608648777008},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2966636121273041},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19458219408988953},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.17233923077583313},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08729991316795349},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0},{"id":"https://openalex.org/C67692717","wikidata":"https://www.wikidata.org/wiki/Q187444","display_name":"Low-density parity-check code","level":3,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C46462455","wikidata":"https://www.wikidata.org/wiki/Q5395712","display_name":"Error floor","level":4,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2017.7953331","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2017.7953331","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":22,"referenced_works":["https://openalex.org/W118372337","https://openalex.org/W1510355813","https://openalex.org/W1607198972","https://openalex.org/W1995875735","https://openalex.org/W2022686119","https://openalex.org/W2099471712","https://openalex.org/W2107503352","https://openalex.org/W2119173531","https://openalex.org/W2181347294","https://openalex.org/W2259795255","https://openalex.org/W2526391956","https://openalex.org/W2566505556","https://openalex.org/W2962810929","https://openalex.org/W3023553154","https://openalex.org/W3038022805","https://openalex.org/W4210992409","https://openalex.org/W4230367971","https://openalex.org/W4231109964","https://openalex.org/W4318977982","https://openalex.org/W4320013936","https://openalex.org/W6685777803","https://openalex.org/W6780248173"],"related_works":["https://openalex.org/W4300005474","https://openalex.org/W2568387792","https://openalex.org/W2115202431","https://openalex.org/W3021680043","https://openalex.org/W2493155480","https://openalex.org/W2045917976","https://openalex.org/W2041838698","https://openalex.org/W4244268987","https://openalex.org/W68624368","https://openalex.org/W2364472724"],"abstract_inverted_index":{"It":[0],"is":[1,93],"almost":[2],"seventy":[3],"years":[4],"after":[5],"the":[6,37,57,69,81,87,103],"publication":[7],"of":[8,14,24,32,39,59,71,89,105],"Claude":[9],"Shannon's":[10],"\u201cA":[11],"Mathematical":[12],"Theory":[13],"Communication\u201d":[15],"[1]":[16],"and":[17,22,34,44,53,65,95],"Norbert":[18],"Wiener's":[19,54],"\u201cExtrapolation,":[20],"Interpolation":[21],"Smoothing":[23],"Stationary":[25],"Time":[26],"Series\u201d":[27],"[2].":[28],"The":[29],"pioneering":[30],"works":[31],"Shannon":[33,52],"Wiener":[35],"lay":[36],"foundation":[38],"communication,":[40],"data":[41],"storage,":[42],"control,":[43],"other":[45],"information":[46,82,91],"technologies.":[47],"This":[48],"paper":[49],"briefly":[50],"reviews":[51],"perspectives":[55,75],"on":[56],"problem":[58],"message":[60],"transmission":[61],"over":[62],"noisy":[63],"channel":[64],"also":[66],"experimentally":[67],"evaluates":[68],"feasibility":[70],"integrating":[72],"these":[73],"two":[74],"to":[76,80,97],"train":[77],"autoencoders":[78],"close":[79],"limit.":[83],"To":[84],"this":[85],"end,":[86],"principle":[88],"relevant":[90],"(PRI)":[92],"used":[94],"validated":[96],"optimally":[98],"encode":[99],"input":[100],"imagery":[101],"in":[102],"presence":[104],"noise.":[106]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}