{"id":"https://openalex.org/W2112043762","doi":"https://doi.org/10.1109/icdsp.2007.4288512","title":"A Unifying Approach to the Derivation of the Class of PNLMS Algorithms","display_name":"A Unifying Approach to the Derivation of the Class of PNLMS Algorithms","publication_year":2007,"publication_date":"2007-07-01","ids":{"openalex":"https://openalex.org/W2112043762","doi":"https://doi.org/10.1109/icdsp.2007.4288512","mag":"2112043762"},"language":"en","primary_location":{"id":"doi:10.1109/icdsp.2007.4288512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2007.4288512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 15th International Conference on Digital Signal Processing","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/A5025470623","display_name":"Beth Jelfs","orcid":"https://orcid.org/0000-0002-6844-7154"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Beth Jelfs","raw_affiliation_strings":["Department of Electrical & Electronic Engineering, Imperial College London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical & Electronic Engineering, Imperial College London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103001848","display_name":"Danilo P. Mandic","orcid":"https://orcid.org/0000-0001-8432-3963"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Danilo P. Mandic","raw_affiliation_strings":["Department of Electrical & Electronic Engineering, Imperial College London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical & Electronic Engineering, Imperial College London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018676117","display_name":"Andrzej Cichocki","orcid":"https://orcid.org/0000-0002-8364-7226"},"institutions":[{"id":"https://openalex.org/I2800939219","display_name":"RIKEN Center for Brain Science","ror":"https://ror.org/04j1n1c04","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800939219","https://openalex.org/I4210110652"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Andrzej Cichocki","raw_affiliation_strings":["RIKEN, Brain Science Institute, Saitama, JAPAN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RIKEN, Brain Science Institute, Saitama, JAPAN","institution_ids":["https://openalex.org/I2800939219"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"35","last_page":"38"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9998999834060669,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9998999834060669,"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":0.998199999332428,"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":0.989300012588501,"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/algorithm","display_name":"Algorithm","score":0.6825530529022217},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6433848738670349},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5530192255973816},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5141997337341309},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.5086370706558228},{"id":"https://openalex.org/keywords/least-mean-squares-filter","display_name":"Least mean squares filter","score":0.4885426461696625},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44703546166419983},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.129754900932312}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6825530529022217},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6433848738670349},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5530192255973816},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5141997337341309},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.5086370706558228},{"id":"https://openalex.org/C32617633","wikidata":"https://www.wikidata.org/wiki/Q1426666","display_name":"Least mean squares filter","level":3,"score":0.4885426461696625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44703546166419983},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.129754900932312},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icdsp.2007.4288512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2007.4288512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 15th International Conference on Digital Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:1324177","is_oa":false,"landing_page_url":"http://discovery.ucl.ac.uk/1324177/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"In: Sanei, S and Chambers, JA and McWhirter, J and Hicks, Y and Constantinides, AG, (eds.) Proceedings of the 2007 15th International Conference on Digital Signal Processing. (pp. 35 - 38). IEEE (2007)","raw_type":"Proceedings paper"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7300000190734863,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W271314235","https://openalex.org/W1489793438","https://openalex.org/W1492221128","https://openalex.org/W1514159701","https://openalex.org/W1555108748","https://openalex.org/W1999542175","https://openalex.org/W2089606495","https://openalex.org/W2096943642","https://openalex.org/W2099464104","https://openalex.org/W2129629082","https://openalex.org/W2143643945","https://openalex.org/W2482792214","https://openalex.org/W2489292218","https://openalex.org/W4285719527","https://openalex.org/W6633124479"],"related_works":["https://openalex.org/W2287235845","https://openalex.org/W2586228848","https://openalex.org/W2081837274","https://openalex.org/W2253481662","https://openalex.org/W1998353256","https://openalex.org/W2357454918","https://openalex.org/W2189195857","https://openalex.org/W3040496336","https://openalex.org/W2370278301","https://openalex.org/W2146261928"],"abstract_inverted_index":{"unifying":[0],"approach":[1,84],"to":[2,41,65,90],"the":[3,6,26,61,66,69,74,79,104],"derivation":[4],"of":[5,8,23,48,78,94],"class":[7,22],"proportionate":[9],"normalised":[10],"least":[11],"mean":[12],"square":[13],"(PNLMS)":[14],"algorithms":[15,24,30,44],"is":[16,19,35,39,53,85],"provided.":[17],"This":[18,52],"an":[20,49],"important":[21],"where":[25],"two":[27],"most":[28],"used":[29],"are":[31],"introduced":[32],"empirically.":[33],"It":[34],"shown":[36],"that":[37],"it":[38],"possible":[40],"derive":[42],"PNLMS":[43,67],"as":[45],"a":[46,56],"result":[47],"optimisation":[50],"procedure.":[51],"achieved":[54],"in":[55,72],"rigorous":[57],"way,":[58],"starting":[59],"from":[60],"standard":[62],"LMS":[63,92],"through":[64],"with":[68],"\"sparsification\"":[70],"factor":[71],"both":[73],"numerator":[75],"and":[76,87],"denominator":[77],"weight":[80],"update.":[81],"The":[82],"proposed":[83],"generic":[86],"also":[88],"applies":[89],"other":[91],"types":[93],"adaptive":[95],"algorithms.":[96],"Simulations":[97],"on":[98],"benchmark":[99],"sparse":[100],"impulse":[101],"responses":[102],"support":[103],"approach.":[105]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-19T07:52:34.831488","created_date":"2025-10-10T00:00:00"}