{"id":"https://openalex.org/W2963858690","doi":"https://doi.org/10.1109/isit.2016.7541721","title":"Coded compressive sensing: A compute-and-recover approach","display_name":"Coded compressive sensing: A compute-and-recover approach","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2963858690","doi":"https://doi.org/10.1109/isit.2016.7541721","mag":"2963858690"},"language":"en","primary_location":{"id":"doi:10.1109/isit.2016.7541721","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2016.7541721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Symposium on Information Theory (ISIT)","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/A5014076559","display_name":"Namyoon Lee","orcid":"https://orcid.org/0000-0003-4321-4108"},"institutions":[{"id":"https://openalex.org/I2799736854","display_name":"Nanjing Institute of Technology","ror":"https://ror.org/00n6txq60","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799736854"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Namyoon Lee","raw_affiliation_strings":["School of Mechanical Engineering, Nanjing Institute of Technology, Nanjing, Jiangsu Province, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Nanjing Institute of Technology, Nanjing, Jiangsu Province, China","institution_ids":["https://openalex.org/I2799736854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084652371","display_name":"Song\u2010Nam Hong","orcid":"https://orcid.org/0000-0002-9535-2521"},"institutions":[{"id":"https://openalex.org/I2799736854","display_name":"Nanjing Institute of Technology","ror":"https://ror.org/00n6txq60","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799736854"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Song-Nam Hong","raw_affiliation_strings":["School of Mechanical Engineering, Nanjing Institute of Technology, Nanjing, Jiangsu Province, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Nanjing Institute of Technology, Nanjing, Jiangsu Province, China","institution_ids":["https://openalex.org/I2799736854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5014076559"],"corresponding_institution_ids":["https://openalex.org/I2799736854"],"apc_list":null,"apc_paid":null,"fwci":1.2458,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.79777667,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2359","last_page":"2363"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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":1.0,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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":0.9990000128746033,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.9242440462112427},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.7008101940155029},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6657215356826782},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.5340100526809692},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5248522758483887},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5105768442153931},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49690011143684387},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.49268609285354614},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.46668940782546997},{"id":"https://openalex.org/keywords/lattice","display_name":"Lattice (music)","score":0.43786200881004333},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35775813460350037},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.3251301646232605},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.12615525722503662},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1139916479587555},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10732695460319519},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.08360117673873901}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.9242440462112427},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.7008101940155029},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6657215356826782},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.5340100526809692},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5248522758483887},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5105768442153931},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49690011143684387},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.49268609285354614},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.46668940782546997},{"id":"https://openalex.org/C2781204021","wikidata":"https://www.wikidata.org/wiki/Q6497091","display_name":"Lattice (music)","level":2,"score":0.43786200881004333},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35775813460350037},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3251301646232605},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.12615525722503662},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1139916479587555},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10732695460319519},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.08360117673873901},{"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/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit.2016.7541721","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2016.7541721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Symposium on Information Theory (ISIT)","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/W5029374","https://openalex.org/W1970433783","https://openalex.org/W2005196269","https://openalex.org/W2017761965","https://openalex.org/W2022050621","https://openalex.org/W2047765680","https://openalex.org/W2060430274","https://openalex.org/W2097323375","https://openalex.org/W2112038498","https://openalex.org/W2122374141","https://openalex.org/W2127271355","https://openalex.org/W2142126109","https://openalex.org/W2145096794","https://openalex.org/W2150498905","https://openalex.org/W2158770864","https://openalex.org/W2160979406","https://openalex.org/W2164452299","https://openalex.org/W2264830470","https://openalex.org/W2963217749","https://openalex.org/W2964322027","https://openalex.org/W6600200425","https://openalex.org/W6693085577"],"related_works":["https://openalex.org/W2378166785","https://openalex.org/W2156466545","https://openalex.org/W2379468505","https://openalex.org/W3104324607","https://openalex.org/W2379256376","https://openalex.org/W2107703637","https://openalex.org/W4206981968","https://openalex.org/W1987102304","https://openalex.org/W2308961925","https://openalex.org/W2381127329"],"abstract_inverted_index":{"In":[0,69,87],"this":[1],"paper,":[2],"we":[3,73,150],"propose":[4],"coded":[5,34],"compressive":[6,35,144],"sensing":[7,36,42,145],"that":[8,152],"recovers":[9],"an":[10,117,158],"n-dimensional":[11],"integer":[12],"sparse":[13,61,101],"signal":[14,62,102,129],"vector":[15,22],"from":[16,63],"a":[17,40,52,108,147],"noisy":[18,65],"and":[19,66,132],"quantized":[20,67],"measurement":[21],"whose":[23,44],"dimension":[24,130],"m":[25,137],"is":[26,37,93,111],"far-fewer":[27],"than":[28],"n.":[29],"The":[30],"core":[31],"idea":[32],"of":[33,47,84,107,135],"to":[38,58,98],"construct":[39],"linear":[41],"matrix":[43],"columns":[45],"consist":[46],"lattice":[48,85],"codes.":[49],"We":[50],"present":[51],"two-stage":[53],"decoding":[54,92],"method":[55],"named":[56],"compute-and-recover":[57],"detect":[59],"the":[60,64,70,82,88,96,100,120,124,128,133,139,153],"measurements.":[68],"first":[71],"stage,":[72,90],"transform":[74],"such":[75],"measurements":[76,80,136],"into":[77],"noiseless":[78],"finite-field":[79,97],"using":[81],"linearity":[83],"codewords.":[86],"second":[89],"syndrome":[91],"applied":[94],"over":[95],"reconstruct":[99],"vector.":[103],"A":[104],"sufficient":[105],"condition":[106],"perfect":[109,140],"recovery":[110,161],"derived.":[112],"Our":[113],"theoretical":[114],"result":[115],"demonstrates":[116],"interplay":[118],"among":[119],"quantization":[121],"level":[122,126],"p,":[123],"sparsity":[125],"k,":[127],"n,":[131],"number":[134],"for":[138],"recovery.":[141],"Considering":[142],"1-bit":[143],"as":[146],"special":[148],"case,":[149],"show":[151],"proposed":[154],"algorithm":[155],"empirically":[156],"outperforms":[157],"existing":[159],"greedy":[160],"algorithm.":[162]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
