{"id":"https://openalex.org/W2583733925","doi":"https://doi.org/10.1109/icassp.1977.1170246","title":"New algorithms for digital convolution","display_name":"New algorithms for digital convolution","publication_year":2005,"publication_date":"2005-03-24","ids":{"openalex":"https://openalex.org/W2583733925","doi":"https://doi.org/10.1109/icassp.1977.1170246","mag":"2583733925"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1977.1170246","doi":"https://doi.org/10.1109/icassp.1977.1170246","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1977.1170246","pdf_url":null,"source":{"id":"https://openalex.org/S4363607879","display_name":"IEEE International Conference on Acoustics Speech and Signal Processing","issn_l":"1520-6149","issn":["1520-6149","2379-190X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-2","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '77. IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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":null,"display_name":"R. Agarwal","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R. Agarwal","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073921563","display_name":"James W. Cooley","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. Cooley","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210114115"],"apc_list":null,"apc_paid":null,"fwci":5.3426,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.96882039,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":"2","issue":null,"first_page":"360","last_page":"362"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11034","display_name":"Digital Filter Design and Implementation","score":0.986299991607666,"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"}},"topics":[{"id":"https://openalex.org/T11034","display_name":"Digital Filter Design and Implementation","score":0.986299991607666,"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/T11693","display_name":"Cryptography and Residue Arithmetic","score":0.0071000000461936,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11210","display_name":"Mathematical Analysis and Transform Methods","score":0.0007999999797903001,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/digital-convolution","display_name":"digital convolution","score":0.9169999957084656},{"id":"https://openalex.org/keywords/chinese-remainder-theorem","display_name":"Chinese remainder theorem","score":0.9169999957084656},{"id":"https://openalex.org/keywords/cyclic-convolution","display_name":"cyclic convolution","score":0.9399999976158142},{"id":"https://openalex.org/keywords/number-theoretic-transform","display_name":"number theoretic transform","score":0.9819999933242798},{"id":"https://openalex.org/keywords/fast-fourier-transform-comparison","display_name":"fast Fourier transform comparison","score":0.7789999842643738},{"id":"https://openalex.org/keywords/winograd-algorithm","display_name":"Winograd algorithm","score":0.5849999785423279},{"id":"https://openalex.org/keywords/computational-efficiency","display_name":"computational efficiency","score":0.5339999794960022}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7986334562301636},{"id":"https://openalex.org/C75172450","wikidata":"https://www.wikidata.org/wiki/Q623950","display_name":"Fast Fourier transform","level":2,"score":0.7149227857589722},{"id":"https://openalex.org/C79587385","wikidata":"https://www.wikidata.org/wiki/Q2638931","display_name":"Convolution theorem","level":5,"score":0.6345417499542236},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6217151880264282},{"id":"https://openalex.org/C194980680","wikidata":"https://www.wikidata.org/wiki/Q245450","display_name":"Circular convolution","level":5,"score":0.6056749224662781},{"id":"https://openalex.org/C151635116","wikidata":"https://www.wikidata.org/wiki/Q193878","display_name":"Chinese remainder theorem","level":2,"score":0.6004300117492676},{"id":"https://openalex.org/C181002996","wikidata":"https://www.wikidata.org/wiki/Q1611641","display_name":"Overlap\u2013add method","level":5,"score":0.5610874891281128},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5589879751205444},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5051489472389221},{"id":"https://openalex.org/C57733114","wikidata":"https://www.wikidata.org/wiki/Q1006032","display_name":"Discrete Fourier transform (general)","level":5,"score":0.4919319152832031},{"id":"https://openalex.org/C122444316","wikidata":"https://www.wikidata.org/wiki/Q1440048","display_name":"Discrete-time Fourier transform","level":5,"score":0.4724205732345581},{"id":"https://openalex.org/C39613435","wikidata":"https://www.wikidata.org/wiki/Q846677","display_name":"Remainder","level":2,"score":0.4722311496734619},{"id":"https://openalex.org/C69598009","wikidata":"https://www.wikidata.org/wiki/Q7280126","display_name":"Rader's FFT algorithm","level":5,"score":0.4555888772010803},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.38295599818229675},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3653852641582489},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.29783740639686584},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.19655001163482666},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.13918745517730713},{"id":"https://openalex.org/C76563020","wikidata":"https://www.wikidata.org/wiki/Q4817582","display_name":"Fractional Fourier transform","level":4,"score":0.09524595737457275},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.1977.1170246","doi":"https://doi.org/10.1109/icassp.1977.1170246","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1977.1170246","pdf_url":null,"source":{"id":"https://openalex.org/S4363607879","display_name":"IEEE International Conference on Acoustics Speech and Signal Processing","issn_l":"1520-6149","issn":["1520-6149","2379-190X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-2","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '77. IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":1,"referenced_works":["https://openalex.org/W2005015931"],"related_works":["https://openalex.org/W2112745636","https://openalex.org/W2116775208","https://openalex.org/W2376344542","https://openalex.org/W1570542763","https://openalex.org/W2117465275","https://openalex.org/W2097787813","https://openalex.org/W4246508376","https://openalex.org/W1964710096","https://openalex.org/W2127146205","https://openalex.org/W1986580622"],"abstract_inverted_index":{"It":[0],"is":[1,23,70],"shown":[2,71],"how":[3],"the":[4,35,42,56,59,73,85,93,116],"Chinese":[5],"Remainder":[6],"Theorem":[7],"(CRT)":[8],"can":[9,63,75],"be":[10,76],"used":[11],"to":[12,18,54,129],"convert":[13],"a":[14,19],"one-dimensional":[15],"cyclic":[16,24],"convolution":[17,21],"multi-dimensional":[20],"which":[22,61],"in":[25,39,52,100],"all":[26],"dimensions.":[27,43],"Then,":[28],"special":[29],"algorithms":[30],"are":[31,96,127],"developed":[32],"which,":[33],"compute":[34,64],"relatively":[36],"short":[37,94,131],"convolutions":[38,60,95],"each":[40],"of":[41,58,92,110,113,120],"The":[44],"original":[45],"suggestion":[46],"for":[47,79,124],"this":[48],"procedure":[49],"was":[50],"made":[51],"order":[53],"extend":[55],"lengths":[57],"one":[62],"with":[65],"number-theoretic":[66],"transforms.":[67],"However,":[68],"it":[69],"that":[72],"method":[74],"more":[77],"efficient,":[78],"some":[80],"data":[81],"sequence":[82],"lengths,":[83],"than":[84],"fast":[86],"Fourier":[87],"transform":[88],"(FFT)":[89],"algorithm.":[90],"Some":[91],"computed":[97],"by":[98,104],"methods":[99,123],"an":[101],"earlier":[102],"paper":[103],"Agarwal":[105],"and":[106,122],"Burrus.":[107],"Recent":[108],"work":[109],"Winograd,":[111],"consisting":[112],"theorems":[114],"giving":[115],"minimum":[117],"possible":[118],"numbers":[119],"multiplications":[121],"achieving":[125],"them,":[126],"applied":[128],"these":[130],"convolutions.":[132]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-11-03T10:50:19.383937","created_date":"2017-02-10T00:00:00"}
