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dc.contributor.authorPaulraj, Murugesa Pandian, Dr.
dc.contributor.authorAbdul Hamid, Adom, Prof., Dr.
dc.contributor.authorSundararaj, Sathishkumar
dc.contributor.authorNorasmadi, Abdul Rahim
dc.date.accessioned2013-07-23T07:40:33Z
dc.date.available2013-07-23T07:40:33Z
dc.date.issued2012-11-20
dc.identifier.citationp. 173-177en_US
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/27001
dc.descriptionMalaysian Technical Universities Conference on Engineering and Technology (MUCET) 2012 organised by technical universities under the Malaysian Technical Universities Network (MTUN), 20th - 21st November 2012 at Hotel Seri Malaysia, Kangar, Perlis.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.publisherMalaysian Technical Universities Network (MTUN)en_US
dc.relation.ispartofseriesProceedings of the Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2012en_US
dc.subjectDifferentially Hearing Ability Enabled (DHAE)en_US
dc.subjectProbabilistic neural network (PNN)en_US
dc.subjectAutoregressive modelen_US
dc.subjectAcoustic sound signatureen_US
dc.titleMoving vehicle recognition and classification based on time domain approachen_US
dc.typeWorking Paperen_US
dc.contributor.urlpaul@unimap.edu.myen_US


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