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dc.contributor.authorPaulraj, Murugesa Pandiyan, Prof. Dr.
dc.contributor.authorAbd Hamid, Adom, Prof. Dr.
dc.contributor.authorSathishkumar, Sundararaj
dc.contributor.authorNorasmadi, Abdul Rahim
dc.date.accessioned2013-08-05T02:29:10Z
dc.date.available2013-08-05T02:29:10Z
dc.date.issued2013
dc.identifier.citationProcedia Engineering, 2013, vol. 53, pages 405–410en_US
dc.identifier.issn1877-7058
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S1877705813001720
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/27385
dc.descriptionLink to publisher's homepage at http://www.elsevier.com/en_US
dc.description.abstractDifferentially Hearing Ability Enabled (DHAE) community cannot discriminate the sound information from a moving vehicle approaching from their behind. This research work is mainly focused on recognition of different vehicles and its position using noise emanated from the vehicle A simple experimental protocol has been designed to record the sound signal emanated from the moving vehicle under different environment conditions and also at different vehicle speed Autoregressive modeling algorithm is used for the analysis to extract the features from the recorded vehicle noise signal. Probabilistic neural network (PNN) models are developed to classify the vehicle type and its distance. The effectiveness of the network is validated through stimulation.en_US
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.subjectDifferentially hearing ability enabled (DHAE)en_US
dc.subjectAcoustic sound signatureen_US
dc.subjectAutoregressive modelen_US
dc.subjectProbabilistic neural network (PNN)en_US
dc.titleMoving vehicle recognition and classification based on time domain approachen_US
dc.typeArticleen_US
dc.contributor.urlpaul@unimap.edu.myen_US
dc.contributor.urlnorasmadi@unimap.edu.myen_US


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