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dc.contributor.authorPaulraj, Murugesa Pandiyan, Prof. Dr.
dc.contributor.authorAbd Hamid, Adom, Prof. Dr.
dc.contributor.authorSiti Marhainis, Othman
dc.contributor.authorSathishkumar, Sundararaj
dc.date.accessioned2014-04-07T05:10:16Z
dc.date.available2014-04-07T05:10:16Z
dc.date.issued2014
dc.identifier.citationApplied Mechanics and Materials, vol.471, 2014, 208-212en_US
dc.identifier.issn1662-7482
dc.identifier.urihttp://dspace.unimap.edu.my:80/dspace/handle/123456789/33465
dc.descriptionLink to publisher's homepage at http://www.ttp.net/en_US
dc.description.abstractThe Hearing Impaired People (HIP) cannot distinguish the sound from a moving vehicle approaching from their behind. Since, it is difficult for hearing impaired to hear and judge sound information and they often encounter risky situations while they are in outdoor. If HIPs can successfully get sound information through some machine interface, dangerous situation will be avoided. Generally the profoundly deaf people do not use any hearing aid which does not provide any benefit. This paper presents, simple statistical features are used to classify the vehicle type and its distance based on sound signature recorded from the moving vehicles. An experimental protocol is designed to record the vehicle sound under different environment conditions and also at different speed of vehicles. Basic statistical features such as the standard deviation, Skewness, Kurtosis and frame energy have been used to extract the features. 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.publisherTrans Tech Publicationsen_US
dc.subjectHearing impaireden_US
dc.subjectProbabilistic Neural Network (PNN)en_US
dc.subjectStatistical featuresen_US
dc.titleMoving vehicle detection using time domain statistical featuresen_US
dc.typeArticleen_US
dc.identifier.urlhttp://www.scientific.net/AMM.471.208
dc.identifier.doi10.4028/www.scientific.net/AMM.471.208
dc.contributor.urlsathishy2j@yahoo.comen_US


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