{"id":"https://openalex.org/W2983839323","doi":"https://doi.org/10.23919/eusipco.2019.8903129","title":"A Novel Design Method for Digital FIR/IIR Filters Based on the Shuffle Frog-Leaping Algorithm","display_name":"A Novel Design Method for Digital FIR/IIR Filters Based on the Shuffle Frog-Leaping Algorithm","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2983839323","doi":"https://doi.org/10.23919/eusipco.2019.8903129","mag":"2983839323"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2019.8903129","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2019.8903129","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2411.19074","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086245031","display_name":"Daniel Jimenez-Galindo","orcid":null},"institutions":[{"id":"https://openalex.org/I108103353","display_name":"Universidad de Valladolid","ror":"https://ror.org/01fvbaw18","country_code":"ES","type":"education","lineage":["https://openalex.org/I108103353"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Daniel Jimenez-Galindo","raw_affiliation_strings":["Universidad de Valladolid, Valladolid, Spain"],"affiliations":[{"raw_affiliation_string":"Universidad de Valladolid, Valladolid, Spain","institution_ids":["https://openalex.org/I108103353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059609720","display_name":"Pablo Casaseca\u2010de\u2010la\u2010Higuera","orcid":"https://orcid.org/0000-0003-1565-0842"},"institutions":[{"id":"https://openalex.org/I108103353","display_name":"Universidad de Valladolid","ror":"https://ror.org/01fvbaw18","country_code":"ES","type":"education","lineage":["https://openalex.org/I108103353"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Pablo Casaseca-de-la-Higuera","raw_affiliation_strings":["Dept. Signal Theory and Communications, Universidad de Valladolid, Valladolid, Spain"],"affiliations":[{"raw_affiliation_string":"Dept. Signal Theory and Communications, Universidad de Valladolid, Valladolid, Spain","institution_ids":["https://openalex.org/I108103353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054395251","display_name":"Luis M. San\u2010Jos\u00e9\u2010Revuelta","orcid":"https://orcid.org/0000-0002-8760-9577"},"institutions":[{"id":"https://openalex.org/I108103353","display_name":"Universidad de Valladolid","ror":"https://ror.org/01fvbaw18","country_code":"ES","type":"education","lineage":["https://openalex.org/I108103353"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Luis M. San-Jose-Revuelta","raw_affiliation_strings":["Dept. Signal Theory and Communications, Universidad de Valladolid, Valladolid, Spain"],"affiliations":[{"raw_affiliation_string":"Dept. Signal Theory and Communications, Universidad de Valladolid, Valladolid, Spain","institution_ids":["https://openalex.org/I108103353"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5086245031"],"corresponding_institution_ids":["https://openalex.org/I108103353"],"apc_list":null,"apc_paid":null,"fwci":0.1447,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59408303,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/infinite-impulse-response","display_name":"Infinite impulse response","score":0.828140139579773},{"id":"https://openalex.org/keywords/finite-impulse-response","display_name":"Finite impulse response","score":0.6242789626121521},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.5733039975166321},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5645784139633179},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49451538920402527},{"id":"https://openalex.org/keywords/digital-filter","display_name":"Digital filter","score":0.47552254796028137},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4650270938873291},{"id":"https://openalex.org/keywords/differential-evolution","display_name":"Differential evolution","score":0.422676146030426},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4063951075077057},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36498352885246277}],"concepts":[{"id":"https://openalex.org/C183816354","wikidata":"https://www.wikidata.org/wiki/Q665617","display_name":"Infinite impulse response","level":4,"score":0.828140139579773},{"id":"https://openalex.org/C198386975","wikidata":"https://www.wikidata.org/wiki/Q117785","display_name":"Finite impulse response","level":2,"score":0.6242789626121521},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.5733039975166321},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5645784139633179},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49451538920402527},{"id":"https://openalex.org/C36390408","wikidata":"https://www.wikidata.org/wiki/Q1163067","display_name":"Digital filter","level":3,"score":0.47552254796028137},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4650270938873291},{"id":"https://openalex.org/C74750220","wikidata":"https://www.wikidata.org/wiki/Q2662197","display_name":"Differential evolution","level":2,"score":0.422676146030426},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4063951075077057},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36498352885246277},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.23919/eusipco.2019.8903129","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2019.8903129","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},{"id":"pmh:oai:uvadoc.uva.es:10324/71907","is_oa":false,"landing_page_url":"https://doi.org/10.23919/EUSIPCO.2019.8903129","pdf_url":null,"source":{"id":"https://openalex.org/S4306401553","display_name":"UVaDOC UVaDOC University of Valladolid Documentary Repository (University of Valladolid)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I108103353","host_organization_name":"Universidad de Valladolid","host_organization_lineage":["https://openalex.org/I108103353"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/acceptedVersion"},{"id":"pmh:oai:arXiv.org:2411.19074","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2411.19074","pdf_url":"https://arxiv.org/pdf/2411.19074","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2411.19074","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2411.19074","pdf_url":"https://arxiv.org/pdf/2411.19074","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2983839323.pdf","grobid_xml":"https://content.openalex.org/works/W2983839323.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W1588959569","https://openalex.org/W2038411763","https://openalex.org/W2063375245","https://openalex.org/W2065689458","https://openalex.org/W2091798611","https://openalex.org/W2105217850","https://openalex.org/W2140416406","https://openalex.org/W2171211995","https://openalex.org/W2201510288","https://openalex.org/W2790121922","https://openalex.org/W6687985135"],"related_works":["https://openalex.org/W4312785053","https://openalex.org/W2142009384","https://openalex.org/W3140661709","https://openalex.org/W2021631062","https://openalex.org/W3138047207","https://openalex.org/W2810377961","https://openalex.org/W2031892245","https://openalex.org/W3208746183","https://openalex.org/W2898725502","https://openalex.org/W2058863651"],"abstract_inverted_index":{"The":[0],"design":[1,34],"of":[2,35,58],"both":[3],"FIR":[4,36],"and":[5,37,88,110],"IIR":[6,38],"digital":[7],"filters":[8,40,68],"is":[9,29],"a":[10,56],"multi-variable":[11],"optimization":[12,105,113],"problem,":[13],"where":[14],"traditional":[15,74],"algorithms":[16,100],"fail":[17],"to":[18,45],"obtain":[19],"optimal":[20],"solutions.":[21],"A":[22],"modified":[23],"Shuffled":[24],"Frog":[25],"Leaping":[26],"Algorithm":[27],"(SFLA)":[28],"here":[30],"proposed":[31],"for":[32],"the":[33,46,66,73],"discrete-time":[39],"as":[41,43,102],"close":[42,86],"possible":[44],"desired":[47],"filter":[48],"frequency":[49],"response.":[50],"This":[51],"algorithm":[52],"can":[53],"be":[54],"considered":[55],"type":[57],"memetic":[59],"algorithm.":[60],"In":[61],"this":[62],"paper,":[63],"simulations":[64],"prove":[65],"obtained":[67],"outperform":[69],"those":[70,93],"designed":[71],"using":[72,99],"bilinear":[75],"Z":[76],"transform":[77],"(BZT)":[78],"method":[79],"with":[80],"elliptic":[81],"approximation.":[82],"Besides,":[83],"results":[84],"are":[85],"to,":[87],"even":[89],"slightly":[90],"better,":[91],"than":[92],"reported":[94],"in":[95],"recent":[96],"bio-inspired":[97],"approaches":[98],"such":[101],"particle":[103],"swarm":[104],"(PSO),":[106],"differential":[107],"evolution":[108],"(DE)":[109],"regularized":[111],"global":[112],"(RGA).":[114]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}