Classification of the Transient Signals via Auditory Representations

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dc.contributor.authorTeolis, A.en_US
dc.contributor.authorShamma, S.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T09:48:55Z
dc.date.available2007-05-23T09:48:55Z
dc.date.issued1991en_US
dc.description.abstractWe use a model of processing in the human auditory system to develop robust representations of signals. These reduced representations are then presented to a neural network for training and classification.<P>Empirical studies demonstrate that auditory representations compare favorably to direct frequency (magnitude spectrum) representations with respect to classification performance (i.e. probabilities of detection and false alarm). For this comparison the Receiver Operating Characteristic (ROC) curves are generated from signals derived from the standard transient data set (STDS) distributed by DARPA/ONR.en_US
dc.format.extent717230 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5145
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1991-99en_US
dc.subjectdetectionen_US
dc.subjectneural systemsen_US
dc.subjectrobust information processingen_US
dc.subjectsignal processingen_US
dc.subjectspeech processingen_US
dc.subjectCommunication en_US
dc.subjectSignal Processing Systemsen_US
dc.titleClassification of the Transient Signals via Auditory Representationsen_US
dc.typeTechnical Reporten_US

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