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Car cabin interior noise classification using temporal composite features and probabilistic neural network model

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Main Authors: Paulraj, Murugesa Pandiyan, Prof. Dr., Allan Melvin, Andrew, Sazali, Yaacob, Prof. Dr.
Other Authors: allanmelvin.andrew@gmail.com
Format: Article
Language:English
Published: Trans Tech Publications Inc. 2014
Subjects:
Frequency band
Neural Network (NN)
Noise comfort
Subjective evaluation
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/34713
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spelling my.unimap-347132014-05-25T07:13:12Z Car cabin interior noise classification using temporal composite features and probabilistic neural network model Paulraj, Murugesa Pandiyan, Prof. Dr. Allan Melvin, Andrew Sazali, Yaacob, Prof. Dr. allanmelvin.andrew@gmail.com Frequency band Neural Network (NN) Noise comfort Subjective evaluation Link to publisher's homepage at http://www.ttp.net/ Determination of vehicle comfort is important because continuous exposure to the noise and vibration leads to health problems for the driver and passengers. In this paper, a vehicle comfort level classification system has been proposed to detect the comfort level in cars using artificial neural network. A database consisting of sound samples obtained from 30 local cars is used. In the stationary condition, the sound pressure level is measured at 1300 RPM, 2000 RPM and 3000 RPM. In the moving condition, the sound is recorded while the car is moving at 30 km/h up to 110 km/h. Subjective test is conducted to find the Jurys evaluation for the specific sound sample. The correlation between the subjective and the objective evaluation is also tested. The relationship between the subjective results and the sound metrics is modelled using Probabilistic Neural Network. It is found from the research that the Temporal Composite Feature gives better classification accuracy for both stationary and moving condition model, 89.51% and 85.61% respectively. 2014-05-25T07:13:12Z 2014-05-25T07:13:12Z 2014 Article Applied Mechanics and Materials, vol.471, 2014, pages 464-68 1662-7482 http://dspace.unimap.edu.my:80/dspace/handle/123456789/34713 http://www.scientific.net/AMM.471.64 10.4028/www.scientific.net/AMM.471.64 en Trans Tech Publications Inc.
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Frequency band
Neural Network (NN)
Noise comfort
Subjective evaluation
spellingShingle Frequency band
Neural Network (NN)
Noise comfort
Subjective evaluation
Paulraj, Murugesa Pandiyan, Prof. Dr.
Allan Melvin, Andrew
Sazali, Yaacob, Prof. Dr.
Car cabin interior noise classification using temporal composite features and probabilistic neural network model
description Link to publisher's homepage at http://www.ttp.net/
author2 allanmelvin.andrew@gmail.com
author_facet allanmelvin.andrew@gmail.com
Paulraj, Murugesa Pandiyan, Prof. Dr.
Allan Melvin, Andrew
Sazali, Yaacob, Prof. Dr.
format Article
author Paulraj, Murugesa Pandiyan, Prof. Dr.
Allan Melvin, Andrew
Sazali, Yaacob, Prof. Dr.
author_sort Paulraj, Murugesa Pandiyan, Prof. Dr.
title Car cabin interior noise classification using temporal composite features and probabilistic neural network model
title_short Car cabin interior noise classification using temporal composite features and probabilistic neural network model
title_full Car cabin interior noise classification using temporal composite features and probabilistic neural network model
title_fullStr Car cabin interior noise classification using temporal composite features and probabilistic neural network model
title_full_unstemmed Car cabin interior noise classification using temporal composite features and probabilistic neural network model
title_sort car cabin interior noise classification using temporal composite features and probabilistic neural network model
publisher Trans Tech Publications Inc.
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/34713
_version_ 1643797566749409280
score 13.209306

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