{"id":"https://openalex.org/W3160108228","doi":"https://doi.org/10.1109/kst51265.2021.9415855","title":"A Deep Learning Approach to Digital Filter Parameter Estimation Based on Amplitude Responses","display_name":"A Deep Learning Approach to Digital Filter Parameter Estimation Based on Amplitude Responses","publication_year":2021,"publication_date":"2021-01-21","ids":{"openalex":"https://openalex.org/W3160108228","doi":"https://doi.org/10.1109/kst51265.2021.9415855","mag":"3160108228"},"language":"en","primary_location":{"id":"doi:10.1109/kst51265.2021.9415855","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kst51265.2021.9415855","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 13th International Conference on Knowledge and Smart Technology (KST)","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/A5027677650","display_name":"Poonna Yospanya","orcid":"https://orcid.org/0000-0002-9457-6937"},"institutions":[{"id":"https://openalex.org/I91538806","display_name":"King Mongkut's Institute of Technology Ladkrabang","ror":"https://ror.org/055mf0v62","country_code":"TH","type":"education","lineage":["https://openalex.org/I91538806"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Poonna Yospanya","raw_affiliation_strings":["Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand","institution_ids":["https://openalex.org/I91538806"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110289199","display_name":"Sorawat Chivapreecha","orcid":null},"institutions":[{"id":"https://openalex.org/I91538806","display_name":"King Mongkut's Institute of Technology Ladkrabang","ror":"https://ror.org/055mf0v62","country_code":"TH","type":"education","lineage":["https://openalex.org/I91538806"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Sorawat Chivapreecha","raw_affiliation_strings":["Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand","institution_ids":["https://openalex.org/I91538806"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063950129","display_name":"Thitaphan Jongsataporn","orcid":null},"institutions":[{"id":"https://openalex.org/I82828225","display_name":"King Mongkut's University of Technology North Bangkok","ror":"https://ror.org/04fy6jb97","country_code":"TH","type":"education","lineage":["https://openalex.org/I82828225"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Thitaphan Jongsataporn","raw_affiliation_strings":["Faculty of Applied Science, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand"],"affiliations":[{"raw_affiliation_string":"Faculty of Applied Science, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand","institution_ids":["https://openalex.org/I82828225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027677650"],"corresponding_institution_ids":["https://openalex.org/I91538806"],"apc_list":null,"apc_paid":null,"fwci":0.3047,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51818796,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"10","issue":null,"first_page":"243","last_page":"248"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9991999864578247,"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/T10860","display_name":"Speech and Audio Processing","score":0.9991999864578247,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9983999729156494,"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/computer-science","display_name":"Computer science","score":0.7119635343551636},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6539215445518494},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.6500087380409241},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.6388304233551025},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6184287667274475},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5474503636360168},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5374845266342163},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5143071413040161},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47622257471084595},{"id":"https://openalex.org/keywords/digital-filter","display_name":"Digital filter","score":0.4708021879196167},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46751195192337036},{"id":"https://openalex.org/keywords/amplitude","display_name":"Amplitude","score":0.44394341111183167},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4258388578891754},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38463786244392395},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.09144803881645203}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7119635343551636},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6539215445518494},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.6500087380409241},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.6388304233551025},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6184287667274475},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5474503636360168},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5374845266342163},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5143071413040161},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47622257471084595},{"id":"https://openalex.org/C36390408","wikidata":"https://www.wikidata.org/wiki/Q1163067","display_name":"Digital filter","level":3,"score":0.4708021879196167},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46751195192337036},{"id":"https://openalex.org/C180205008","wikidata":"https://www.wikidata.org/wiki/Q159190","display_name":"Amplitude","level":2,"score":0.44394341111183167},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4258388578891754},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38463786244392395},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.09144803881645203},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/kst51265.2021.9415855","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kst51265.2021.9415855","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 13th International Conference on Knowledge and Smart Technology (KST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2112796928","https://openalex.org/W2163605009","https://openalex.org/W2606176153","https://openalex.org/W2613718673","https://openalex.org/W2618530766","https://openalex.org/W2754165686","https://openalex.org/W2796347433","https://openalex.org/W2897524142","https://openalex.org/W2969372706","https://openalex.org/W2972162845","https://openalex.org/W2981443492","https://openalex.org/W2995233853","https://openalex.org/W3000389243","https://openalex.org/W3000751478","https://openalex.org/W3005904649","https://openalex.org/W3015635148","https://openalex.org/W3015759143","https://openalex.org/W4293584584","https://openalex.org/W6736723571","https://openalex.org/W6769233789","https://openalex.org/W6773821797"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"our":[3],"attempt":[4],"to":[5,95],"tackle":[6],"the":[7,56,67,74,97],"problem":[8],"of":[9,19,59,86],"digital":[10],"filter":[11,24],"type":[12],"and":[13,34],"parameter":[14],"estimation":[15],"given":[16],"a":[17,23,43,52,62],"set":[18],"points":[20],"sampled":[21],"from":[22,30],"frequency":[25],"response.":[26],"We":[27],"compared":[28],"results":[29,40],"various":[31],"multilayer":[32,63],"perceptron":[33,64],"convolutional":[35,44],"neural":[36,45],"network":[37,46],"configurations.":[38],"The":[39],"suggest":[41],"that":[42],"generally":[47],"produces":[48],"faster":[49],"convergence":[50],"with":[51],"lower":[53],"loss":[54],"at":[55],"same":[57],"number":[58],"epochs":[60],"than":[61],"network.":[65],"However,":[66],"maximum":[68],"amplitude":[69],"response":[70],"error,":[71],"which":[72],"is":[73,93],"true":[75],"performance":[76],"metrics,":[77],"can":[78],"be":[79],"comparable":[80],"in":[81],"some":[82],"cases.":[83],"A":[84],"combination":[85],"multiple":[87],"best-performing":[88],"configurations":[89],"for":[90],"different":[91],"tasks":[92],"used":[94],"assemble":[96],"final":[98],"model.":[99]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
