{"dcterms:modified":"2023-07-19","dcterms:creator":"DR-NTU (Data)","@type":"ore:ResourceMap","@id":"https://researchdata.ntu.edu.sg/api/datasets/export?exporter=OAI_ORE&persistentId=doi:10.21979/N9/ETJWLU","ore:describes":{"dateOfDeposit":"2023-03-16","kindOfData":"Dataset","subject":"Engineering","citation:depositor":"Luo Zhengding","title":"Synthetic noise dataset","citation:dsDescription":{"citation:dsDescriptionValue":"The synthetic noise dataset is divided into 3 subsets: 80,000 noise tracks for training, 2,000 noise tracks for validation, and remaining 2,000 noise tracks for testing. The synthetic noise tracks are generated by filtering white noise through various band-pass filters with randomly chosen center frequencies and bandwidths. Each noise track in the dataset has a 1-second duration with a sample rate of 16 kHz."},"publication":{"publicationCitation":"Luo, Z., Shi, D., & Gan, W. S. (2022). A Hybrid SFANC-FxNLMS Algorithm for Active Noise Control Based on Deep Learning. IEEE Signal Processing Letters, 29, 1102-1106.","publicationIDType":"doi","publicationIDNumber":"10.1109/LSP.2022.3169428","publicationURL":"https://ieeexplore.ieee.org/abstract/document/9761749"},"software":{"citation:softwareName":"Python"},"citation:datasetContact":{"citation:datasetContactName":"Luo Zhengding","citation:datasetContactAffiliation":"Nanyang Technological University"},"author":[{"citation:authorName":"Luo, Zhengding","citation:authorAffiliation":"Nanyang Technological University","authorIdentifierScheme":"ORCID","authorIdentifier":"0000-0002-2694-5059"},{"citation:authorName":"Shi, Dongyuan","citation:authorAffiliation":"Nanyang Technological University","authorIdentifierScheme":"ORCID","authorIdentifier":"0000-0003-0768-6386"},{"citation:authorName":"Gan, Woon-Seng","citation:authorAffiliation":"Nanyang Technological University","authorIdentifierScheme":"ORCID","authorIdentifier":"0000-0002-7143-1823"}],"citation:keyword":{"citation:keywordValue":"Synthetic noise dataset"},"@id":"doi:10.21979/N9/ETJWLU","@type":["ore:Aggregation","schema:Dataset"],"schema:version":"1.0","schema:name":"Synthetic noise dataset","schema:dateModified":"Fri Mar 17 09:09:18 SGT 2023","schema:datePublished":"2023-03-16","schema:license":"http://creativecommons.org/licenses/by-nc/4.0","dvcore:fileTermsOfAccess":{"dvcore:fileRequestAccess":false},"schema:includedInDataCatalog":"DR-NTU (Data)","ore:aggregates":[{"schema:name":"Synthesized_Dataset.zip","dvcore:restricted":false,"schema:version":1,"dvcore:datasetVersionId":6793,"@id":"https://researchdata.ntu.edu.sg/file.xhtml?fileId=109950","schema:sameAs":"https://researchdata.ntu.edu.sg/api/access/datafile/109950","@type":"ore:AggregatedResource","schema:fileFormat":"application/zip","dvcore:filesize":5002898000,"dvcore:storageIdentifier":"file://186e9ac776d-c7437837e43a","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"7294321fdda1ee2fb41ca4cfe1ae033f"}}],"schema:hasPart":["https://researchdata.ntu.edu.sg/file.xhtml?fileId=109950"]},"@context":{"author":"http://purl.org/dc/terms/creator","authorIdentifier":"http://purl.org/spar/datacite/AgentIdentifier","authorIdentifierScheme":"http://purl.org/spar/datacite/AgentIdentifierScheme","citation":"https://dataverse.org/schema/citation/","dateOfDeposit":"http://purl.org/dc/terms/dateSubmitted","dcterms":"http://purl.org/dc/terms/","dvcore":"https://dataverse.org/schema/core#","kindOfData":"http://rdf-vocabulary.ddialliance.org/discovery#kindOfData","ore":"http://www.openarchives.org/ore/terms/","publication":"http://purl.org/dc/terms/isReferencedBy","publicationCitation":"http://purl.org/dc/terms/bibliographicCitation","publicationIDNumber":"http://purl.org/spar/datacite/ResourceIdentifier","publicationIDType":"http://purl.org/spar/datacite/ResourceIdentifierScheme","publicationURL":"https://schema.org/distribution","schema":"http://schema.org/","software":"https://www.w3.org/TR/prov-o/#wasGeneratedBy","subject":"http://purl.org/dc/terms/subject","title":"http://purl.org/dc/terms/title"}}