Adaptive noise cancellation by LMS algorithm

The research on controlling the noise level in an environment has been the focus of many researchers over the last few years. Adaptive noise cancellation (ANC) is one such approach that has been proposed for reduction of steady state noise. In this research, the least mean square (LMS) algorithm...

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Main Author: Saon, Sharifah
Format: Thesis
Language:English
English
English
Published: 2004
Subjects:
Online Access:http://eprints.uthm.edu.my/8631/
Abstract Abstract here
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author Saon, Sharifah
author_facet Saon, Sharifah
author_sort Saon, Sharifah
description The research on controlling the noise level in an environment has been the focus of many researchers over the last few years. Adaptive noise cancellation (ANC) is one such approach that has been proposed for reduction of steady state noise. In this research, the least mean square (LMS) algorithm using MATLAB was implemented. Step size determination was done to determine the best step size and effects of the rate of convergence. Sound recorder was used to record sound and saved as .wav file. Graphical user interface (GUI) was created to make it user friendly. The output of the analysis showed that the best step size was 0.008. Smaller step size of 0.001 tend to lower the speed of convergence, and too big a step size, 0.8 tend to cause the system to diverge. Analysis on synthesized data showed that the noise reduction did not eliminate the original signal. The implementation on actual data showed slight difference between the output and input level. In real situation, as in theory, this technique can be used to reduce noise level from noisy signal without reducing the characteristic of the signal.
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spelling uthm-86312023-05-02T02:11:57Z http://eprints.uthm.edu.my/8631/ Adaptive noise cancellation by LMS algorithm Saon, Sharifah TD Environmental technology. Sanitary engineering TD878-894 Special types of environment, Including soil pollution, air pollution, noise pollution The research on controlling the noise level in an environment has been the focus of many researchers over the last few years. Adaptive noise cancellation (ANC) is one such approach that has been proposed for reduction of steady state noise. In this research, the least mean square (LMS) algorithm using MATLAB was implemented. Step size determination was done to determine the best step size and effects of the rate of convergence. Sound recorder was used to record sound and saved as .wav file. Graphical user interface (GUI) was created to make it user friendly. The output of the analysis showed that the best step size was 0.008. Smaller step size of 0.001 tend to lower the speed of convergence, and too big a step size, 0.8 tend to cause the system to diverge. Analysis on synthesized data showed that the noise reduction did not eliminate the original signal. The implementation on actual data showed slight difference between the output and input level. In real situation, as in theory, this technique can be used to reduce noise level from noisy signal without reducing the characteristic of the signal. 2004-04 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/8631/1/24p%20SHARIFAH%20SAON.pdf text en http://eprints.uthm.edu.my/8631/2/SHARIFAH%20SAON%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/8631/3/SHARIFAH%20SAON%20WATERMARK.pdf Saon, Sharifah (2004) Adaptive noise cancellation by LMS algorithm. Masters thesis, Kolej Universiti Teknologi Tun Hussein Onn.
spellingShingle TD Environmental technology. Sanitary engineering
TD878-894 Special types of environment, Including soil pollution, air pollution, noise pollution
Saon, Sharifah
Adaptive noise cancellation by LMS algorithm
thesis_level Master
title Adaptive noise cancellation by LMS algorithm
title_full Adaptive noise cancellation by LMS algorithm
title_fullStr Adaptive noise cancellation by LMS algorithm
title_full_unstemmed Adaptive noise cancellation by LMS algorithm
title_short Adaptive noise cancellation by LMS algorithm
title_sort adaptive noise cancellation by lms algorithm
topic TD Environmental technology. Sanitary engineering
TD878-894 Special types of environment, Including soil pollution, air pollution, noise pollution
url http://eprints.uthm.edu.my/8631/
work_keys_str_mv AT saonsharifah adaptivenoisecancellationbylmsalgorithm