{"id":"https://openalex.org/W4323065866","doi":"https://doi.org/10.1109/lsp.2023.3252469","title":"A Correlation Coefficient Sparsity Adaptive Matching Pursuit Algorithm","display_name":"A Correlation Coefficient Sparsity Adaptive Matching Pursuit Algorithm","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4323065866","doi":"https://doi.org/10.1109/lsp.2023.3252469"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2023.3252469","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2023.3252469","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-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/A5075574423","display_name":"Yanjun Li","orcid":"https://orcid.org/0000-0001-5220-2286"},"institutions":[{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanjun Li","raw_affiliation_strings":["Beijing Institute of Remote Sensing Equipment, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Remote Sensing Equipment, Beijing, China","institution_ids":["https://openalex.org/I4210166112"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101455556","display_name":"Wendong Chen","orcid":"https://orcid.org/0000-0001-8636-4558"},"institutions":[{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wendong Chen","raw_affiliation_strings":["Beijing Institute of Remote Sensing Equipment, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Remote Sensing Equipment, Beijing, China","institution_ids":["https://openalex.org/I4210166112"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5075574423"],"corresponding_institution_ids":["https://openalex.org/I4210166112"],"apc_list":null,"apc_paid":null,"fwci":3.0275,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.91150161,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"30","issue":null,"first_page":"190","last_page":"194"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9991999864578247,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9990000128746033,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.7401116490364075},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.7143502235412598},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.6721037030220032},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.6675372123718262},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6022523641586304},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5272616147994995},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.523457944393158},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.4735131561756134},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.4516321122646332},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.44190114736557007},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44031766057014465},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4307234287261963},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.42258796095848083},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4151616394519806},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4106995165348053},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38433319330215454},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37566912174224854},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.24345868825912476},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09906020760536194}],"concepts":[{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.7401116490364075},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.7143502235412598},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.6721037030220032},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6675372123718262},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6022523641586304},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5272616147994995},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.523457944393158},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.4735131561756134},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.4516321122646332},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.44190114736557007},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44031766057014465},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4307234287261963},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.42258796095848083},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4151616394519806},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4106995165348053},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38433319330215454},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37566912174224854},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.24345868825912476},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09906020760536194},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2023.3252469","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2023.3252469","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8700000047683716,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1527917680","https://openalex.org/W2042241484","https://openalex.org/W2046658845","https://openalex.org/W2095978736","https://openalex.org/W2100037283","https://openalex.org/W2145096794","https://openalex.org/W2289917018","https://openalex.org/W2314695925","https://openalex.org/W2509943785","https://openalex.org/W2543316627","https://openalex.org/W2973239615","https://openalex.org/W3004984540","https://openalex.org/W3009611541","https://openalex.org/W3016207974","https://openalex.org/W3157702020","https://openalex.org/W3185560379","https://openalex.org/W3213001039","https://openalex.org/W4200620882","https://openalex.org/W4250955649","https://openalex.org/W4283220775","https://openalex.org/W6631772773"],"related_works":["https://openalex.org/W2378166785","https://openalex.org/W2382972663","https://openalex.org/W2388133936","https://openalex.org/W2465351041","https://openalex.org/W1555738523","https://openalex.org/W2103001330","https://openalex.org/W2946877649","https://openalex.org/W2340242818","https://openalex.org/W4200575023","https://openalex.org/W2012574959"],"abstract_inverted_index":{"This":[0,54],"paper":[1],"presents":[2],"a":[3,57],"correlation":[4,72,95,104],"coefficient":[5,105],"sparsity":[6,18],"adaptive":[7,19],"matching":[8,20],"pursuit":[9,21],"(CCSAMP)":[10],"algorithm":[11,69],"for":[12,59,152],"practical":[13,61],"compressed":[14],"sensing":[15],"(CS).":[16],"The":[17,30,67,87,109,147],"(SAMP)":[22],"has":[23],"been":[24],"enhanced":[25],"using":[26],"the":[27,36,76,81,100,103,112,118,128,133,138,144],"CCSAMP":[28,110,134,148],"algorithm.":[29,146],"CCSAMP's":[31],"capacity":[32],"to":[33,48,99,143],"accurately":[34],"reconstruct":[35],"signal":[37,122],"with":[38],"fewer":[39],"repetitions":[40],"is":[41,90,106,168],"its":[42],"most":[43],"novel":[44],"characteristic":[45],"when":[46],"compared":[47,142],"other":[49,159],"state-of-the-art":[50],"SAMP":[51,145],"enhancement":[52],"methods.":[53],"makes":[55],"it":[56],"candidate":[58,85],"many":[60],"applications":[62],"that":[63,132],"need":[64],"fast":[65,162],"reconstruction.":[66],"proposed":[68],"constructs":[70],"two":[71],"vectors,":[73],"which":[74],"represent":[75],"input":[77],"signals":[78,167],"recovered":[79],"from":[80],"support":[82],"set":[83],"and":[84,158,163],"set.":[86],"step":[88],"size":[89],"transformed":[91],"by":[92],"their":[93],"Pearson":[94],"coefficients":[96],"(PCCS).":[97],"Compared":[98],"residual":[101],"energy,":[102],"more":[107],"sensitive.":[108],"reduces":[111],"number":[113,139],"of":[114,121,127,140,166],"iterations":[115,141],"while":[116],"maintaining":[117],"SAMP's":[119],"capability":[120],"reconstruction":[123,165],"without":[124],"prior":[125],"knowledge":[126],"sparsity.":[129],"Simulation":[130],"shows":[131],"can":[135,149],"significantly":[136],"reduce":[137],"be":[150],"used":[151],"radar":[153,155],"detection,":[154],"3D":[156],"imaging,":[157],"fields":[160],"where":[161],"accurate":[164],"required.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}