Urban noise classification of active noise control system for residential buildings
In this report, various audio signal features are extracted and combined into different sets to be examined. Feature set that produces highest accuracy is to be chosen as optimal features applied in support vector machine (SVM) classifier to classify noises around residential buildings. The designed...
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| التنسيق: | Final Year Project |
| اللغة: | English |
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2019
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10356/77342 |
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sg-ntu-dr.10356-773422023-07-07T17:37:55Z Urban noise classification of active noise control system for residential buildings Cui, Jing Fang Gan Woon Seng School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering In this report, various audio signal features are extracted and combined into different sets to be examined. Feature set that produces highest accuracy is to be chosen as optimal features applied in support vector machine (SVM) classifier to classify noises around residential buildings. The designed noise classification system is the premier approach to provide relevant coefficients for active noise control filter in an active noise control (ANC) system. Based on the experiment conducted in this paper, the ultimate trained SVM classification model classifies noises that can reache an accuracy around 95%. Bachelor of Engineering (Electrical and Electronic Engineering) 2019-05-27T07:15:18Z 2019-05-27T07:15:18Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77342 en Nanyang Technological University 59 p. application/pdf |
| institution |
Nanyang Technological University |
| building |
NTU Library |
| continent |
Asia |
| country |
Singapore Singapore |
| content_provider |
NTU Library |
| collection |
DR-NTU |
| language |
English |
| topic |
DRNTU::Engineering::Electrical and electronic engineering |
| spellingShingle |
DRNTU::Engineering::Electrical and electronic engineering Cui, Jing Fang Urban noise classification of active noise control system for residential buildings |
| description |
In this report, various audio signal features are extracted and combined into different sets to be examined. Feature set that produces highest accuracy is to be chosen as optimal features applied in support vector machine (SVM) classifier to classify noises around residential buildings. The designed noise classification system is the premier approach to provide relevant coefficients for active noise control filter in an active noise control (ANC) system. Based on the experiment conducted in this paper, the ultimate trained SVM classification model classifies noises that can reache an accuracy around 95%. |
| author2 |
Gan Woon Seng |
| author_facet |
Gan Woon Seng Cui, Jing Fang |
| format |
Final Year Project |
| author |
Cui, Jing Fang |
| author_sort |
Cui, Jing Fang |
| title |
Urban noise classification of active noise control system for residential buildings |
| title_short |
Urban noise classification of active noise control system for residential buildings |
| title_full |
Urban noise classification of active noise control system for residential buildings |
| title_fullStr |
Urban noise classification of active noise control system for residential buildings |
| title_full_unstemmed |
Urban noise classification of active noise control system for residential buildings |
| title_sort |
urban noise classification of active noise control system for residential buildings |
| publishDate |
2019 |
| url |
http://hdl.handle.net/10356/77342 |
| _version_ |
1772825836374720512 |