{"id":"https://openalex.org/W2024744079","doi":"https://doi.org/10.1109/icassp.2014.6853757","title":"Compressed matched filter for non-Gaussian noise","display_name":"Compressed matched filter for non-Gaussian noise","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2024744079","doi":"https://doi.org/10.1109/icassp.2014.6853757","mag":"2024744079"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2014.6853757","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6853757","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5019003834","display_name":"Jakob Vovnoboy","orcid":"https://orcid.org/0000-0001-5423-1478"},"institutions":[{"id":"https://openalex.org/I197251160","display_name":"Hebrew University of Jerusalem","ror":"https://ror.org/03qxff017","country_code":"IL","type":"education","lineage":["https://openalex.org/I197251160"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Jakob Vovnoboy","raw_affiliation_strings":["The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem","Rachel and Selim Benin School of Computer Science and Engineering, Hebrew University of Jerusalem, Jerusalem, Israel"],"affiliations":[{"raw_affiliation_string":"The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem","institution_ids":["https://openalex.org/I197251160"]},{"raw_affiliation_string":"Rachel and Selim Benin School of Computer Science and Engineering, Hebrew University of Jerusalem, Jerusalem, Israel","institution_ids":["https://openalex.org/I197251160"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091732723","display_name":"Ami Wiesel","orcid":"https://orcid.org/0000-0002-3071-048X"},"institutions":[{"id":"https://openalex.org/I197251160","display_name":"Hebrew University of Jerusalem","ror":"https://ror.org/03qxff017","country_code":"IL","type":"education","lineage":["https://openalex.org/I197251160"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Ami Wiesel","raw_affiliation_strings":["The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem","Rachel and Selim Benin School of Computer Science and Engineering, Hebrew University of Jerusalem, Jerusalem, Israel"],"affiliations":[{"raw_affiliation_string":"The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem","institution_ids":["https://openalex.org/I197251160"]},{"raw_affiliation_string":"Rachel and Selim Benin School of Computer Science and Engineering, Hebrew University of Jerusalem, Jerusalem, Israel","institution_ids":["https://openalex.org/I197251160"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5019003834"],"corresponding_institution_ids":["https://openalex.org/I197251160"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.08625257,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1050","last_page":"1054"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9955000281333923,"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":0.9941999912261963,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6044996976852417},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.599663496017456},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.588058352470398},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5553120374679565},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5370401740074158},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5070393085479736},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.46711409091949463},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4563082754611969},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.4488987922668457},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.43935030698776245},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.42946138978004456},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4201717972755432},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36444902420043945},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36154788732528687},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1879793405532837},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.09312063455581665}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6044996976852417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.599663496017456},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.588058352470398},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5553120374679565},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5370401740074158},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5070393085479736},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.46711409091949463},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4563082754611969},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.4488987922668457},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.43935030698776245},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.42946138978004456},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4201717972755432},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36444902420043945},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36154788732528687},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1879793405532837},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.09312063455581665},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2014.6853757","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6853757","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1971340117","https://openalex.org/W2025742588","https://openalex.org/W2040637789","https://openalex.org/W2046033161","https://openalex.org/W2084840427","https://openalex.org/W2095872233","https://openalex.org/W2100556411","https://openalex.org/W2101223300","https://openalex.org/W2104266187","https://openalex.org/W2119495655","https://openalex.org/W2122475628","https://openalex.org/W2133301970","https://openalex.org/W2135046866","https://openalex.org/W2152139090","https://openalex.org/W2156395862","https://openalex.org/W2161310686","https://openalex.org/W2165155912","https://openalex.org/W4238202755"],"related_works":["https://openalex.org/W1542224353","https://openalex.org/W1661087619","https://openalex.org/W2116854923","https://openalex.org/W2750730210","https://openalex.org/W2236974868","https://openalex.org/W4312766348","https://openalex.org/W2158224665","https://openalex.org/W4233939244","https://openalex.org/W2730764323","https://openalex.org/W2133587243"],"abstract_inverted_index":{"We":[0,76,111],"consider":[1],"estimation":[2],"of":[3,115],"a":[4,10,23,28,45,58,64,72,79],"deterministic":[5],"unknown":[6,49],"parameter":[7],"vector":[8],"in":[9,50],"linear":[11,24],"model":[12],"with":[13,63],"non-Gaussian":[14,53],"noise.":[15],"In":[16],"the":[17,51,94,108,113,116],"Gaussian":[18],"case,":[19],"dimensionality":[20],"reduction":[21],"via":[22],"matched":[25,60],"filter":[26,61],"provides":[27],"simple":[29],"low":[30,73],"dimensional":[31,74],"sufficient":[32],"statistic":[33,46],"which":[34,69,101],"can":[35],"be":[36],"easily":[37],"communicated":[38],"and/or":[39],"stored":[40],"for":[41,82,104],"future":[42],"inference.":[43],"Such":[44],"is":[47,91,102],"usually":[48],"general":[52],"case.":[54],"Instead,":[55],"we":[56],"propose":[57],"hybrid":[59],"coupled":[62],"randomized":[65],"compressed":[66,109],"sensing":[67],"procedure,":[68],"together":[70],"create":[71],"statistic.":[75,87],"also":[77],"derive":[78],"complementary":[80],"algorithm":[81,100],"robust":[83],"reconstruction":[84],"given":[85,107],"this":[86],"Our":[88],"recovery":[89],"method":[90],"based":[92],"on":[93],"fast":[95],"iterative":[96],"shrinkage":[97],"and":[98],"thresholding":[99],"used":[103],"outlier":[105],"rejection":[106],"data.":[110],"demonstrate":[112],"advantages":[114],"proposed":[117],"framework":[118],"using":[119],"synthetic":[120],"simulations.":[121]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
