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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Bibliographic Details
Main Author:	Cui, Jing Fang
Other Authors:	Gan Woon Seng
Format:	Final Year Project
Language:	English
Published:	2019
Subjects:	DRNTU::Engineering::Electrical and electronic engineering
Online Access:	http://hdl.handle.net/10356/77342
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Institution:	Nanyang Technological University
Language:	English

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record_format	dspace
spelling	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

Urban noise classification of active noise control system for residential buildings

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