{"id":"https://openalex.org/W2059964364","doi":"https://doi.org/10.1109/icassp.2013.6638711","title":"Sample allocation for statistical multiresolution compressed sensing","display_name":"Sample allocation for statistical multiresolution compressed sensing","publication_year":2013,"publication_date":"2013-05-01","ids":{"openalex":"https://openalex.org/W2059964364","doi":"https://doi.org/10.1109/icassp.2013.6638711","mag":"2059964364"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2013.6638711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6638711","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","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/A5047724448","display_name":"Chunli Guo","orcid":"https://orcid.org/0000-0001-5056-7951"},"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":true,"raw_author_name":"Chunli Guo","raw_affiliation_strings":["School of Engineering and Electronics, University of Edinburgh, UK","Sch. of Eng. & Electron., Univ. of Edinburgh, Edinburgh, , UK"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Electronics, University of Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"Sch. of Eng. & Electron., Univ. of Edinburgh, Edinburgh, , UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057962470","display_name":"Mike E. Davies","orcid":"https://orcid.org/0000-0003-2327-236X"},"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":"Mike E. Davies","raw_affiliation_strings":["School of Engineering and Electronics, University of Edinburgh, UK","Sch. of Eng. & Electron., Univ. of Edinburgh, Edinburgh, , UK"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Electronics, University of Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"Sch. of Eng. & Electron., Univ. of Edinburgh, Edinburgh, , UK","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5047724448"],"corresponding_institution_ids":["https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":0.3455,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62959601,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"10","issue":null,"first_page":"5479","last_page":"5483"},"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":0.9998000264167786,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.686186671257019},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5702247619628906},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5579668879508972},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4683377742767334},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4271222949028015},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.42513507604599},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42051106691360474},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41096752882003784},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3634326457977295}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.686186671257019},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5702247619628906},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5579668879508972},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4683377742767334},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4271222949028015},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.42513507604599},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42051106691360474},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41096752882003784},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3634326457977295},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2013.6638711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6638711","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","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":15,"referenced_works":["https://openalex.org/W1500149156","https://openalex.org/W1989574703","https://openalex.org/W2071284784","https://openalex.org/W2082029531","https://openalex.org/W2083721848","https://openalex.org/W2106684272","https://openalex.org/W2115755118","https://openalex.org/W2123202508","https://openalex.org/W2137813581","https://openalex.org/W2168796889","https://openalex.org/W2963206527","https://openalex.org/W3100456593","https://openalex.org/W3100706365","https://openalex.org/W3105033759","https://openalex.org/W3140876134"],"related_works":["https://openalex.org/W2382174632","https://openalex.org/W2129959498","https://openalex.org/W2784060934","https://openalex.org/W2902714807","https://openalex.org/W2537489131","https://openalex.org/W2394084632","https://openalex.org/W2358293514","https://openalex.org/W2046633342","https://openalex.org/W2014650515","https://openalex.org/W2539623612"],"abstract_inverted_index":{"We":[0,54],"model":[1],"the":[2,6,14,19,28,32,40,57,64,69,72,86],"compressible":[3],"signal":[4],"with":[5,68],"two":[7],"states":[8],"Gaussian":[9],"mixture":[10],"distribution":[11],"and":[12,44],"consider":[13],"sample":[15,46,66],"distortion":[16],"function":[17,43],"for":[18,49],"recently":[20],"proposed":[21],"Bayesian":[22],"optimal":[23],"AMP":[24,33],"decoder.":[25],"By":[26],"leveraging":[27],"rigorous":[29],"analysis":[30],"of":[31,71,77,90],"algorithm,":[34],"we":[35],"are":[36],"able":[37],"to":[38,62],"derive":[39],"theoretical":[41],"SD":[42],"a":[45],"allocation":[47,67],"scheme":[48],"multi-resolution":[50],"statistical":[51],"image":[52,83],"model.":[53],"then":[55],"adopt":[56],"\u201cturbo\u201d":[58],"message":[59],"passing":[60],"method":[61],"integrate":[63],"bandwise":[65],"exploitation":[70],"hidden":[73],"Markov":[74],"tree":[75],"structure":[76],"wavelet":[78],"coefficients.":[79],"Experiments":[80],"on":[81],"natural":[82],"show":[84],"that":[85],"combination":[87],"outperforms":[88],"either":[89],"them":[91],"working":[92],"alone.":[93]},"counts_by_year":[{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}