{"id":"https://openalex.org/W2127536479","doi":"https://doi.org/10.1109/nnsp.2002.1030043","title":"An adaptive approach to wavelet filters design","display_name":"An adaptive approach to wavelet filters design","publication_year":2003,"publication_date":"2003-06-25","ids":{"openalex":"https://openalex.org/W2127536479","doi":"https://doi.org/10.1109/nnsp.2002.1030043","mag":"2127536479"},"language":"en","primary_location":{"id":"doi:10.1109/nnsp.2002.1030043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nnsp.2002.1030043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th IEEE Workshop on Neural Networks for 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/A5011198947","display_name":"Nicola Neretti","orcid":"https://orcid.org/0000-0002-9552-1663"},"institutions":[{"id":"https://openalex.org/I27804330","display_name":"Brown University","ror":"https://ror.org/05gq02987","country_code":"US","type":"education","lineage":["https://openalex.org/I27804330"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"N. Neretti","raw_affiliation_strings":["Institute for Brain and Neural Systems, Brown University, Providence, RI, USA","[Institute for Brain and Neural Systems, Brown University, Providence, RI, USA]"],"affiliations":[{"raw_affiliation_string":"Institute for Brain and Neural Systems, Brown University, Providence, RI, USA","institution_ids":["https://openalex.org/I27804330"]},{"raw_affiliation_string":"[Institute for Brain and Neural Systems, Brown University, Providence, RI, USA]","institution_ids":["https://openalex.org/I27804330"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029500893","display_name":"Nathan Intrator","orcid":"https://orcid.org/0000-0002-5635-9835"},"institutions":[{"id":"https://openalex.org/I27804330","display_name":"Brown University","ror":"https://ror.org/05gq02987","country_code":"US","type":"education","lineage":["https://openalex.org/I27804330"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"N. Intrator","raw_affiliation_strings":["Institute for Brain and Neural Systems, Brown University, Providence, RI, USA","[Institute for Brain and Neural Systems, Brown University, Providence, RI, USA]"],"affiliations":[{"raw_affiliation_string":"Institute for Brain and Neural Systems, Brown University, Providence, RI, USA","institution_ids":["https://openalex.org/I27804330"]},{"raw_affiliation_string":"[Institute for Brain and Neural Systems, Brown University, Providence, RI, USA]","institution_ids":["https://openalex.org/I27804330"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5011198947"],"corresponding_institution_ids":["https://openalex.org/I27804330"],"apc_list":null,"apc_paid":null,"fwci":0.2694,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.59993541,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"317","last_page":"326"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","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/T10688","display_name":"Image and Signal Denoising Methods","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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9998000264167786,"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/T11034","display_name":"Digital Filter Design and Implementation","score":0.9979000091552734,"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/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.8587336540222168},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.7970541715621948},{"id":"https://openalex.org/keywords/second-generation-wavelet-transform","display_name":"Second-generation wavelet transform","score":0.7695240378379822},{"id":"https://openalex.org/keywords/stationary-wavelet-transform","display_name":"Stationary wavelet transform","score":0.7025264501571655},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.6984760761260986},{"id":"https://openalex.org/keywords/lifting-scheme","display_name":"Lifting scheme","score":0.6585242748260498},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.6254943609237671},{"id":"https://openalex.org/keywords/cascade-algorithm","display_name":"Cascade algorithm","score":0.6171793937683105},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5369595885276794},{"id":"https://openalex.org/keywords/harmonic-wavelet-transform","display_name":"Harmonic wavelet transform","score":0.5367594361305237},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4511888325214386},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4168984293937683},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37037816643714905},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2685375511646271}],"concepts":[{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.8587336540222168},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.7970541715621948},{"id":"https://openalex.org/C111350171","wikidata":"https://www.wikidata.org/wiki/Q7443700","display_name":"Second-generation wavelet transform","level":5,"score":0.7695240378379822},{"id":"https://openalex.org/C73339587","wikidata":"https://www.wikidata.org/wiki/Q1375942","display_name":"Stationary wavelet transform","level":5,"score":0.7025264501571655},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.6984760761260986},{"id":"https://openalex.org/C199550912","wikidata":"https://www.wikidata.org/wiki/Q3238415","display_name":"Lifting scheme","level":5,"score":0.6585242748260498},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.6254943609237671},{"id":"https://openalex.org/C88829872","wikidata":"https://www.wikidata.org/wiki/Q5048176","display_name":"Cascade algorithm","level":5,"score":0.6171793937683105},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5369595885276794},{"id":"https://openalex.org/C1109138","wikidata":"https://www.wikidata.org/wiki/Q3280930","display_name":"Harmonic wavelet transform","level":5,"score":0.5367594361305237},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4511888325214386},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4168984293937683},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37037816643714905},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2685375511646271}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/nnsp.2002.1030043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nnsp.2002.1030043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.160.918","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.160.918","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.math.tau.ac.il/~nin/papers/ABB30-nnsp2002.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1481646516","https://openalex.org/W1604810369","https://openalex.org/W1658679052","https://openalex.org/W2015370045","https://openalex.org/W2033966461","https://openalex.org/W2146788889","https://openalex.org/W2156447271","https://openalex.org/W4251101141"],"related_works":["https://openalex.org/W2085792030","https://openalex.org/W2391053410","https://openalex.org/W2368320199","https://openalex.org/W2101997086","https://openalex.org/W1889651196","https://openalex.org/W2355386503","https://openalex.org/W2274421086","https://openalex.org/W2073231481","https://openalex.org/W2071357496","https://openalex.org/W2164576153"],"abstract_inverted_index":{"We":[0,36],"present":[1],"a":[2,9,15,20,32,44],"general":[3],"framework":[4],"for":[5,43],"the":[6,53,57,62],"design":[7],"of":[8,22,31,56,61],"mother":[10,58],"wavelet":[11,46,59,63],"best":[12],"adapted":[13],"to":[14,19,52],"specific":[16],"signal":[17],"or":[18],"class":[21],"signals.":[23],"The":[24,48],"filter's":[25],"coefficients":[26],"are":[27],"obtained":[28],"via":[29],"optimization":[30,41,55],"smooth":[33],"objective":[34],"function.":[35],"develop":[37],"an":[38],"unconstrained":[39],"gradient-based":[40],"algorithm":[42,49],"discrete":[45],"transform.":[47],"is":[50],"extended":[51],"joint":[54],"and":[60],"packets":[64],"basis.":[65]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}