Please use this identifier to cite or link to this item:
Title: Urban noise classification of active noise control system for residential buildings
Authors: Cui, Jing Fang
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2019
Abstract: 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%.
Schools: School of Electrical and Electronic Engineering 
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
FYP Final Report(Jing Fang).pdf
  Restricted Access
1.65 MBAdobe PDFView/Open

Page view(s)

Updated on Jun 17, 2024


Updated on Jun 17, 2024

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.