iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://api.openalex.org/works/doi:10.1109/ISIT.2009.5205788
{"id":"https://openalex.org/W2106911957","doi":"https://doi.org/10.1109/isit.2009.5205788","title":"Sparsity-embracing multiuser detection for CDMA systems with low activity factory","display_name":"Sparsity-embracing multiuser detection for CDMA systems with low activity factory","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2106911957","doi":"https://doi.org/10.1109/isit.2009.5205788","mag":"2106911957"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2009.5205788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5100644862","display_name":"Hao Zhu","orcid":"https://orcid.org/0000-0002-1554-5332"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hao Zhu","raw_affiliation_strings":["Department of ECE, University of Minnesota, Minneapolis, 55455 USA"],"affiliations":[{"raw_affiliation_string":"Department of ECE, University of Minnesota, Minneapolis, 55455 USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026758314","display_name":"Georgios B. Giannakis","orcid":"https://orcid.org/0000-0002-0196-0260"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Georgios B. Giannakis","raw_affiliation_strings":["Department of ECE, University of Minnesota, Minneapolis, 55455 USA"],"affiliations":[{"raw_affiliation_string":"Department of ECE, University of Minnesota, Minneapolis, 55455 USA","institution_ids":["https://openalex.org/I130238516"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.922,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":16,"citation_normalized_percentile":{"value":0.802871,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":88},"biblio":{"volume":"58","issue":null,"first_page":"164","last_page":"168"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Theory and Applications of Compressed Sensing","score":0.9999,"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":"Theory and Applications of Compressed Sensing","score":0.9999,"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/T10931","display_name":"Array Processing for Signal Localization and Estimation","score":0.9942,"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":"Decentralized Inference in Wireless Sensor Networks","score":0.9906,"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/sparsity-in-signal-processing","display_name":"Sparsity in Signal Processing","score":0.631869},{"id":"https://openalex.org/keywords/sparse-sensing","display_name":"Sparse Sensing","score":0.570216},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.5485368},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse Approximation","score":0.543946},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed Sensing","score":0.52477},{"id":"https://openalex.org/keywords/sparse-representations","display_name":"Sparse Representations","score":0.519822}],"concepts":[{"id":"https://openalex.org/C47696715","wikidata":"https://www.wikidata.org/wiki/Q233394","display_name":"Code division multiple access","level":2,"score":0.6747225},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6058061},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.5485368},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.54430944},{"id":"https://openalex.org/C2777104032","wikidata":"https://www.wikidata.org/wiki/Q16324514","display_name":"Multiuser detection","level":3,"score":0.5291745},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5059294},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.48682493},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4794318},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36503705},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3393233},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33735338},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18047145},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.14048001},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10986233},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2009.5205788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":13,"referenced_works":["https://openalex.org/W1648445109","https://openalex.org/W1967073510","https://openalex.org/W1986931325","https://openalex.org/W2075081724","https://openalex.org/W2078204800","https://openalex.org/W2104266187","https://openalex.org/W2106911957","https://openalex.org/W2116631972","https://openalex.org/W2129638195","https://openalex.org/W2135046866","https://openalex.org/W2295549646","https://openalex.org/W2912369344","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W4236271946","https://openalex.org/W2614517342","https://openalex.org/W2545278143","https://openalex.org/W2367731216","https://openalex.org/W2171748043","https://openalex.org/W2143469310","https://openalex.org/W1997358463","https://openalex.org/W1965397739","https://openalex.org/W1933375666","https://openalex.org/W174650468"],"abstract_inverted_index":{"The":[0,19,62,132],"number":[1],"of":[2,31,65,98,128,134,143,157,167,178],"active":[3],"users":[4],"in":[5,39,112,124],"code-division":[6],"multiple":[7],"access":[8],"(CDMA)":[9],"systems":[10,139],"is":[11,52,79,140],"often":[12],"much":[13],"lower":[14],"than":[15],"the":[16,55,66,86,95,99,125,154,160,169,176,179],"spreading":[17],"gain.":[18],"present":[20],"paper":[21],"exploits":[22],"fruitfully":[23],"this":[24,135],"a":[25,40,48,70,73,83,141],"priori":[26],"information":[27],"to":[28,58,81,137,172,184],"improve":[29],"performance":[30,149],"multiuser":[32,145],"detectors.":[33],"A":[34],"low-activity":[35],"factor":[36],"manifests":[37],"itself":[38],"sparse":[41],"symbol":[42,57,101],"vector":[43,102,182],"with":[44],"entries":[45,177],"drawn":[46],"from":[47],"finite":[49],"alphabet":[50,68],"that":[51],"augmented":[53,67],"by":[54,94],"zero":[56],"capture":[59],"user":[60],"inactivity.":[61],"non-equiprobable":[63],"symbols":[64],"motivate":[69],"sparsity-exploiting":[71,173],"maximum":[72],"posteriori":[74],"probability":[75],"(S-MAP)":[76],"criterion,":[77],"which":[78],"shown":[80],"yield":[82],"cost":[84],"comprising":[85],"lscr":[87],"2":[90],"least-squares":[91],"error":[92],"penalized":[93],"p-th":[96],"norm":[97],"wanted":[100,180],"(p":[103],"=":[104],"0;":[105],"1;":[106],"2).":[107],"Related":[108],"optimization":[109],"problems":[110],"appear":[111],"variable":[113],"selection":[114,163],"(shrinkage)":[115],"schemes":[116],"developed":[117],"for":[118,150],"linear":[119],"regression,":[120],"as":[121,123],"well":[122],"emerging":[126],"field":[127],"compressive":[129],"sampling":[130],"(CS).":[131],"contribution":[133,170],"work":[136],"CDMA":[138],"gamut":[142],"sparsity-embracing":[144],"detectors":[146],"trading":[147],"off":[148],"complexity":[151],"requirements.":[152],"From":[153],"vantage":[155],"point":[156],"CS":[158],"and":[159],"least-absolute":[161],"shrinkage":[162],"operator":[164],"(Lasso)":[165],"spectrum":[166],"applications,":[168],"amounts":[171],"algorithms":[174],"when":[175],"signal":[181],"adhere":[183],"finite-alphabet":[185],"constraints.":[186]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2106911957","counts_by_year":[{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":5}],"updated_date":"2024-10-13T11:24:23.563449","created_date":"2016-06-24"}