{"id":"https://openalex.org/W2730769158","doi":"https://doi.org/10.1109/siu.2017.7960189","title":"Wavelet-based anomaly detection on digital signals","display_name":"Wavelet-based anomaly detection on digital signals","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2730769158","doi":"https://doi.org/10.1109/siu.2017.7960189","mag":"2730769158"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2017.7960189","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2017.7960189","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th Signal Processing and Communications Applications Conference (SIU)","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/A5100616808","display_name":"\u00d6mer Ayd\u0131n","orcid":"https://orcid.org/0000-0002-7137-4881"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Omer Aydin","raw_affiliation_strings":["Ara\u015ft\u0131rma ve Geli\u015ftirme Departman\u0131, Neta\u015f Telekom\u00fcnikasyon A.\u015e., \u0130stanbul, T\u00fcrkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ara\u015ft\u0131rma ve Geli\u015ftirme Departman\u0131, Neta\u015f Telekom\u00fcnikasyon A.\u015e., \u0130stanbul, T\u00fcrkiye","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022972408","display_name":"Melek Kurnaz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Melek Kurnaz","raw_affiliation_strings":["Ara\u015ft\u0131rma ve Geli\u015ftirme Departman\u0131, Neta\u015f Telekom\u00fcnikasyon A.\u015e., \u0130stanbul, T\u00fcrkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ara\u015ft\u0131rma ve Geli\u015ftirme Departman\u0131, Neta\u015f Telekom\u00fcnikasyon A.\u015e., \u0130stanbul, T\u00fcrkiye","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4131,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.71663478,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"13","issue":null,"first_page":"1","last_page":"3"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9921000003814697,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9646999835968018,"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/oscilloscope","display_name":"Oscilloscope","score":0.7405252456665039},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.7192932963371277},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7098357677459717},{"id":"https://openalex.org/keywords/closing","display_name":"Closing (real estate)","score":0.668792188167572},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6636576652526855},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6482250094413757},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5766902565956116},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5487955808639526},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5440958142280579},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.4700537919998169},{"id":"https://openalex.org/keywords/dilation","display_name":"Dilation (metric space)","score":0.4315285086631775},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4105912446975708},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1406668722629547},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10455447435379028}],"concepts":[{"id":"https://openalex.org/C184026988","wikidata":"https://www.wikidata.org/wiki/Q174320","display_name":"Oscilloscope","level":3,"score":0.7405252456665039},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.7192932963371277},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7098357677459717},{"id":"https://openalex.org/C2778775528","wikidata":"https://www.wikidata.org/wiki/Q5135432","display_name":"Closing (real estate)","level":2,"score":0.668792188167572},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6636576652526855},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6482250094413757},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5766902565956116},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5487955808639526},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5440958142280579},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.4700537919998169},{"id":"https://openalex.org/C2780757906","wikidata":"https://www.wikidata.org/wiki/Q5276676","display_name":"Dilation (metric space)","level":2,"score":0.4315285086631775},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4105912446975708},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1406668722629547},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10455447435379028},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu.2017.7960189","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2017.7960189","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th Signal Processing and Communications Applications Conference (SIU)","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":12,"referenced_works":["https://openalex.org/W35739717","https://openalex.org/W142656147","https://openalex.org/W1510992165","https://openalex.org/W1680008435","https://openalex.org/W2068008363","https://openalex.org/W2087685851","https://openalex.org/W2102583368","https://openalex.org/W2129270900","https://openalex.org/W2164392650","https://openalex.org/W4285719527","https://openalex.org/W6605799428","https://openalex.org/W6683992316"],"related_works":["https://openalex.org/W1972598373","https://openalex.org/W2364019159","https://openalex.org/W1489049788","https://openalex.org/W2243648136","https://openalex.org/W2370764016","https://openalex.org/W3087970328","https://openalex.org/W2355173512","https://openalex.org/W820894194","https://openalex.org/W2785153243","https://openalex.org/W2372413705"],"abstract_inverted_index":{"Since":[0],"today's":[1],"information":[2],"and":[3,24,47,53,75,83],"telecommunication":[4],"devices":[5],"are":[6],"very":[7,22],"complex,":[8],"it":[9],"is":[10,39],"time":[11],"consuming":[12],"task":[13],"to":[14,27,55,78],"find":[15],"anomalies":[16,57],"on":[17,58,66],"digital":[18,59,68],"signals":[19,69],"which":[20,41,70],"happen":[21],"rarely":[23],"not":[25],"easy":[26],"recreate":[28],"by":[29,72],"testing.":[30],"In":[31],"this":[32],"work,":[33],"a":[34],"new":[35],"anomaly":[36],"detection":[37],"method":[38,95],"proposed":[40,94],"includes":[42],"wavelet":[43,62],"transform,":[44],"k-means":[45],"clustering":[46],"morphological":[48],"operators":[49],"such":[50],"as":[51],"closing":[52],"dilation":[54],"detect":[56],"signals.":[60],"After":[61],"decomposition":[63],"was":[64],"performed":[65],"the":[67,73,79,93],"recorded":[71],"oscilloscope":[74],"then":[76],"transferred":[77],"computer,":[80],"unsupervised":[81],"learning":[82],"mathematical":[84],"morphology":[85],"have":[86],"been":[87],"applied.":[88],"Test":[89],"results":[90],"show":[91],"that":[92],"achieves":[96],"high-detection":[97],"rates.":[98]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
