{"id":"https://openalex.org/W3115459768","doi":"https://doi.org/10.23919/eusipco47968.2020.9287602","title":"Gradient of Mutual Information in Linear Vector Gaussian Channels in the Presence of Input Noise","display_name":"Gradient of Mutual Information in Linear Vector Gaussian Channels in the Presence of Input Noise","publication_year":2020,"publication_date":"2020-12-18","ids":{"openalex":"https://openalex.org/W3115459768","doi":"https://doi.org/10.23919/eusipco47968.2020.9287602","mag":"3115459768"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco47968.2020.9287602","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco47968.2020.9287602","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 28th European Signal Processing Conference (EUSIPCO)","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/A5060579838","display_name":"Fraser K. Coutts","orcid":"https://orcid.org/0000-0003-2299-2648"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Fraser K. Coutts","raw_affiliation_strings":["Institute for Digital Communications, University of Edinburgh, Edinburgh, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Digital Communications, University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061430082","display_name":"John Thompson","orcid":"https://orcid.org/0000-0002-4605-9708"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"John Thompson","raw_affiliation_strings":["Institute for Digital Communications, University of Edinburgh, Edinburgh, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Digital Communications, University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076320344","display_name":"B. Mulgrew","orcid":"https://orcid.org/0000-0002-8082-2818"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Bernard Mulgrew","raw_affiliation_strings":["Institute for Digital Communications, University of Edinburgh, Edinburgh, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Digital Communications, University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6083,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.68569006,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"2264","last_page":"2268"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9987000226974487,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11236","display_name":"Control Systems and Identification","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/mutual-information","display_name":"Mutual information","score":0.6904294490814209},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6790128350257874},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6729385852813721},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6171963214874268},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.5243383049964905},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5147321224212646},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.504052996635437},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4678075313568115},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.46313977241516113},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.42613035440444946},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4015239477157593},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.34942781925201416},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.25900155305862427},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2345021665096283},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.17926296591758728},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.12754225730895996},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.10289913415908813}],"concepts":[{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.6904294490814209},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6790128350257874},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6729385852813721},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6171963214874268},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5243383049964905},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5147321224212646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.504052996635437},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4678075313568115},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.46313977241516113},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.42613035440444946},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4015239477157593},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.34942781925201416},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.25900155305862427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2345021665096283},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.17926296591758728},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.12754225730895996},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.10289913415908813},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco47968.2020.9287602","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco47968.2020.9287602","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 28th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1927786901","display_name":null,"funder_award_id":"EP/S000631/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1840522340","https://openalex.org/W2049633694","https://openalex.org/W2069667906","https://openalex.org/W2080598516","https://openalex.org/W2085229299","https://openalex.org/W2097695636","https://openalex.org/W2098316308","https://openalex.org/W2102129292","https://openalex.org/W2110768232","https://openalex.org/W2111616148","https://openalex.org/W2116141292","https://openalex.org/W2119667497","https://openalex.org/W2133775995","https://openalex.org/W2138245406","https://openalex.org/W2141426461","https://openalex.org/W2160773882","https://openalex.org/W2163762663","https://openalex.org/W2164814215","https://openalex.org/W2167455364","https://openalex.org/W2354949621","https://openalex.org/W2568283273","https://openalex.org/W2615863827","https://openalex.org/W2940989281","https://openalex.org/W2951576988","https://openalex.org/W2972209638","https://openalex.org/W3100302110","https://openalex.org/W3101339175","https://openalex.org/W6670501329","https://openalex.org/W6684092480"],"related_works":["https://openalex.org/W1970319972","https://openalex.org/W2489520628","https://openalex.org/W2953254336","https://openalex.org/W2112030392","https://openalex.org/W2986378528","https://openalex.org/W3178345791","https://openalex.org/W2949211747","https://openalex.org/W1550854977","https://openalex.org/W2092661960","https://openalex.org/W2588855097"],"abstract_inverted_index":{"This":[0],"paper":[1],"considers":[2],"a":[3,27,58,69,82,86,109],"general":[4],"linear":[5],"vector":[6],"Gaussian":[7,16,18],"channel":[8],"with":[9,72],"arbitrary":[10],"signalling":[11],"in":[12,81,92],"the":[13,35,51,54,75,89,98],"presence":[14],"of":[15,53],"or":[17,62],"mixture":[19],"input":[20],"noise":[21,24],"-":[22,61,67],"i.e.,":[23],"added":[25],"to":[26,31,74],"desired":[28,59],"signal":[29,60],"prior":[30],"its":[32,63],"measurement.":[33],"Generalising":[34],"fundamental":[36],"relationship":[37],"unveiled":[38],"by":[39,43],"Guo":[40],"and":[41,68],"extended":[42],"Palomar,":[44],"we":[45],"show":[46],"for":[47,88],"this":[48],"scenario":[49],"that":[50,97],"gradient":[52,104,110],"mutual":[55],"information":[56],"between":[57],"discrete":[64],"class":[65],"label":[66],"measured":[70],"output":[71],"respect":[73],"measurement":[76],"matrix":[77],"can":[78,101],"be":[79],"expressed":[80],"novel":[83],"form":[84],"without":[85],"requirement":[87],"approximations":[90],"made":[91],"previous":[93],"papers.":[94],"We":[95],"demonstrate":[96],"derived":[99],"expressions":[100],"outperform":[102],"approximate":[103],"terms":[105],"when":[106],"integrated":[107],"within":[108],"ascent":[111],"multi-objective":[112],"optimisation":[113],"approach.":[114]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}