{"id":"https://openalex.org/W2145369120","doi":"https://doi.org/10.1109/tassp.1986.1164916","title":"A robust running-window detector and estimator for step-signals in contaminated Gaussian noise","display_name":"A robust running-window detector and estimator for step-signals in contaminated Gaussian noise","publication_year":1986,"publication_date":"1986-08-01","ids":{"openalex":"https://openalex.org/W2145369120","doi":"https://doi.org/10.1109/tassp.1986.1164916","mag":"2145369120"},"language":"en","primary_location":{"id":"doi:10.1109/tassp.1986.1164916","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tassp.1986.1164916","pdf_url":null,"source":{"id":"https://openalex.org/S98930721","display_name":"IEEE Transactions on Acoustics Speech and Signal Processing","issn_l":"0096-3518","issn":["0096-3518"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Acoustics, Speech, and Signal Processing","raw_type":"journal-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/A5091404066","display_name":"R.L. Kirlin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R. Kirlin","raw_affiliation_strings":["Department of Electrical Engineering, University of Wurzburg, Laramie, WY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Wurzburg, Laramie, WY, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109149172","display_name":"A. Moghaddamjoo","orcid":null},"institutions":[{"id":"https://openalex.org/I43579087","display_name":"University of Wisconsin\u2013Milwaukee","ror":"https://ror.org/031q21x57","country_code":"US","type":"education","lineage":["https://openalex.org/I43579087"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A. Moghaddamjoo","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Wisconsin, Milwaukee, Milwaukee, WI, USA","Department of Electrical Engineering, University of Wurzburg, Laramie, WY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Wisconsin, Milwaukee, Milwaukee, WI, USA","institution_ids":["https://openalex.org/I43579087"]},{"raw_affiliation_string":"Department of Electrical Engineering, University of Wurzburg, Laramie, WY, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7705,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.8885189,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"34","issue":"4","first_page":"816","last_page":"823"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9977999925613403,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9977999925613403,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9886000156402588,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9815000295639038,"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/noise","display_name":"Noise (video)","score":0.6312640309333801},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6116583347320557},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5731607675552368},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.5433799028396606},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5352160930633545},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5205353498458862},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5070285797119141},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.5060920119285583},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49971628189086914},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4659505784511566},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.44241371750831604},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4422617256641388},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.42651262879371643},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4027985632419586},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37148016691207886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3043779730796814},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1141100823879242},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.105317622423172}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6312640309333801},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6116583347320557},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5731607675552368},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.5433799028396606},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5352160930633545},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5205353498458862},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5070285797119141},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.5060920119285583},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49971628189086914},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4659505784511566},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.44241371750831604},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4422617256641388},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.42651262879371643},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4027985632419586},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37148016691207886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3043779730796814},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1141100823879242},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.105317622423172},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tassp.1986.1164916","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tassp.1986.1164916","pdf_url":null,"source":{"id":"https://openalex.org/S98930721","display_name":"IEEE Transactions on Acoustics Speech and Signal Processing","issn_l":"0096-3518","issn":["0096-3518"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Acoustics, Speech, and Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W25587163","https://openalex.org/W2007148047","https://openalex.org/W2028041217","https://openalex.org/W2045021643","https://openalex.org/W2060605975","https://openalex.org/W2113508851","https://openalex.org/W2122683098","https://openalex.org/W2131184796","https://openalex.org/W2145834063","https://openalex.org/W2168932899","https://openalex.org/W2325343629","https://openalex.org/W2503341991","https://openalex.org/W2800289289","https://openalex.org/W4255444560","https://openalex.org/W4299503428"],"related_works":["https://openalex.org/W2390901981","https://openalex.org/W4230691760","https://openalex.org/W2393847170","https://openalex.org/W85049056","https://openalex.org/W2109115373","https://openalex.org/W577521963","https://openalex.org/W2054277467","https://openalex.org/W2612577981","https://openalex.org/W4210701935","https://openalex.org/W2364775115"],"abstract_inverted_index":{"An":[0],"N-point":[1],"window":[2],"is":[3],"applied":[4],"to":[5,8,27,70,75],"noisy":[6],"data":[7,32],"recover":[9],"stepped":[10],"signals":[11],"in":[12],"non-Gaussian":[13],"noise.":[14],"Robust":[15],"measures":[16],"of":[17,31],"signal":[18,63],"step":[19],"level":[20,64],"and":[21,59,62,79,82],"noise":[22],"distribution":[23],"spread":[24],"are":[25,35,55,66,85],"used":[26],"detect":[28],"sequential":[29],"clusters":[30],"points":[33],"which":[34],"statistically":[36],"significantly":[37],"different,":[38],"thereby":[39],"detecting":[40],"the":[41],"step.":[42],"Using":[43],"conventional":[44],"analysis-of-variance":[45],"methods,":[46],"but":[47],"with":[48],"robust":[49],"parameter":[50],"estimates,":[51],"false":[52],"alarm":[53],"probabilities":[54,61],"set":[56],"reasonably":[57],"accurately,":[58],"miss":[60],"estimates":[65],"shown":[67],"by":[68],"simulation":[69],"yield":[71],"good":[72],"results.":[73],"Applications":[74],"Kalman":[76],"filtering,":[77],"seismic":[78],"well-log":[80],"data,":[81],"image":[83],"processing":[84],"indicated.":[86]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}