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Detection and Classification of Nonstationary Transient Signals Using Sparse Approximations and Bayesian Networks

contributor authorWachowski, Neil
contributor authorAzimi-Sadjadi, Mahmood R.
date accessioned2020-03-13T00:18:47Z
date available2020-03-13T00:18:47Z
date issued2014
identifier issn2329-9290
identifier other6879434.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1142085?show=full
formatgeneral
languageEnglish
publisherIEEE
titleDetection and Classification of Nonstationary Transient Signals Using Sparse Approximations and Bayesian Networks
typeJournal Paper
contenttypeMetadata Only
identifier padid8324571
subject keywordsapproximation theory
subject keywordsbelief networks
subject keywordssignal classification
subject keywordssignal detection
subject keywordsstatistical testing
subject keywordsBayesian networks
subject keywordsadditive noise
subject keywordsassociated hypothesis
subject keywordscomplex sonic environments
subject keywordsgeneralized likelihood ratio tests
subject keywordsmultiple transient signal classification
subject keywordsnational park soundscape analysis problem
subject keywordsnonstationary transient signal classification
subject keywordsnonstationary transient signal detection
subject keywordsquiescent detection
subject keywordsquiescent periods
subject keywordsreal acoustical source classification
subject keywordsreal acoustical source d
identifier doi10.1109/TASLP.2014.2348913
journal titleAudio, Speech, and Language Processing, IEEE/ACM Transactions on
journal volume22
journal issue12
filesize2843118
citations0


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