{"id":"https://openalex.org/W2543348581","doi":"https://doi.org/10.1109/dsp-spe.2015.7369536","title":"Adaptive likelihood codebook reordering vector quantization for 1-D data sources","display_name":"Adaptive likelihood codebook reordering vector quantization for 1-D data sources","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W2543348581","doi":"https://doi.org/10.1109/dsp-spe.2015.7369536","mag":"2543348581"},"language":"en","primary_location":{"id":"doi:10.1109/dsp-spe.2015.7369536","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsp-spe.2015.7369536","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5089867921","display_name":"Chu Meh Chu","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chu Meh Chu","raw_affiliation_strings":["Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005152221","display_name":"Nathan V. Parrish","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nathan V. Parrish","raw_affiliation_strings":["Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033437141","display_name":"David V. Anderson","orcid":"https://orcid.org/0000-0002-8571-4613"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David V. Anderson","raw_affiliation_strings":["Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"93","issue":null,"first_page":"107","last_page":"112"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":1.0,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9970999956130981,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9908999800682068,"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/codebook","display_name":"Codebook","score":0.9774922132492065},{"id":"https://openalex.org/keywords/linde\u2013buzo\u2013gray-algorithm","display_name":"Linde\u2013Buzo\u2013Gray algorithm","score":0.8849833011627197},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.867077648639679},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.58846515417099},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5342549085617065},{"id":"https://openalex.org/keywords/learning-vector-quantization","display_name":"Learning vector quantization","score":0.5283176302909851},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.48967984318733215},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4810533821582794},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.46729519963264465},{"id":"https://openalex.org/keywords/entropy-encoding","display_name":"Entropy encoding","score":0.4639795422554016},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44694846868515015},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4443660378456116},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.43442919850349426},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4144403040409088},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.3121420741081238},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29822784662246704},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07909420132637024}],"concepts":[{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.9774922132492065},{"id":"https://openalex.org/C93372532","wikidata":"https://www.wikidata.org/wiki/Q6552455","display_name":"Linde\u2013Buzo\u2013Gray algorithm","level":3,"score":0.8849833011627197},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.867077648639679},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.58846515417099},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5342549085617065},{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.5283176302909851},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.48967984318733215},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4810533821582794},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.46729519963264465},{"id":"https://openalex.org/C1769480","wikidata":"https://www.wikidata.org/wiki/Q1345239","display_name":"Entropy encoding","level":3,"score":0.4639795422554016},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44694846868515015},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4443660378456116},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.43442919850349426},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4144403040409088},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.3121420741081238},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29822784662246704},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07909420132637024},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsp-spe.2015.7369536","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsp-spe.2015.7369536","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7799999713897705,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1634005169","https://openalex.org/W1635512741","https://openalex.org/W1982047291","https://openalex.org/W2062765737","https://openalex.org/W2131578006","https://openalex.org/W2134383396","https://openalex.org/W2138075982","https://openalex.org/W2163904446","https://openalex.org/W2165824734","https://openalex.org/W2166431488","https://openalex.org/W2504881501","https://openalex.org/W2913399920","https://openalex.org/W4210893461","https://openalex.org/W4244017338"],"related_works":["https://openalex.org/W2017514583","https://openalex.org/W2391875658","https://openalex.org/W2100120615","https://openalex.org/W1929869830","https://openalex.org/W2017401491","https://openalex.org/W2387054321","https://openalex.org/W2158612577","https://openalex.org/W2352648934","https://openalex.org/W2145213141","https://openalex.org/W2170599662"],"abstract_inverted_index":{"This":[0,110],"paper":[1],"outlines":[2],"an":[3,106],"adaptive":[4,83,129],"extension":[5],"of":[6,131],"likelihood":[7,84],"codebook":[8,29,85],"reordering":[9,86],"(LCR)":[10],"vector":[11,20,87],"quantization.":[12],"By":[13],"providing":[14],"a":[15,25,91],"method":[16,111],"for":[17],"allowing":[18],"the":[19,28,46,52,66,90,101,123,128,132],"quantization":[21,88],"to":[22,34,42,55,78,100,122],"adapt":[23],"in":[24,45,59,65,114],"predetermined":[26],"way,":[27],"may":[30],"be":[31,56],"adaptively":[32],"reordered":[33,124],"allow":[35],"more":[36,57],"efficient":[37,58],"encoding":[38],"by":[39],"giving":[40],"preference":[41],"encountered":[43],"vectors":[44],"dictionary.":[47],"In":[48],"particular,":[49],"adaptation":[50],"allows":[51],"trained":[53],"dictionaries":[54],"representing":[60],"specific":[61],"data.":[62],"The":[63,82],"difference":[64],"training":[67,97],"and":[68],"testing":[69,80,102],"sets":[70],"produces":[71],"different":[72],"transition":[73,93],"matrices":[74],"which":[75],"are":[76],"used":[77],"encode":[79],"vectors.":[81],"adapts":[89],"priori":[92],"matrix":[94],"obtained":[95,126],"from":[96,127],"data":[98,103],"set":[99,104],"on":[105],"online":[107],"instantaneous":[108],"basis.":[109],"yields":[112],"improvements":[113],"coding":[115,119],"rate":[116],"when":[117],"entropy":[118],"is":[120],"applied":[121],"indices":[125],"version":[130],"LCR":[133],"algorithm.":[134]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}