PERBANDINGAN MOTHER WAVELET DALAM PROSES DENOISING PADA SUARA
Wavelet Transform is a method that developed for analyzing the nonstationer signal. Wavelet Transform was used in denoising process on speech to enhance the quality of speech that courrupted by noise. The kinds of involved noises are White Gaussian Noise (WGN), White Uniform Noise (WUN) dan Colored...
| Main Authors: | , |
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| Format: | Thesis |
| Published: |
[Yogyakarta] : Universitas Gadjah Mada
2013
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| Subjects: |
| _version_ | 1797033818867105792 |
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| author | , Rahmat Ramadhan , Dr. Agfianto Eko Putra, M. Si. |
| author_facet | , Rahmat Ramadhan , Dr. Agfianto Eko Putra, M. Si. |
| author_sort | , Rahmat Ramadhan |
| collection | UGM |
| description | Wavelet Transform is a method that developed for analyzing the nonstationer
signal. Wavelet Transform was used in denoising process on speech to
enhance the quality of speech that courrupted by noise. The kinds of involved
noises are White Gaussian Noise (WGN), White Uniform Noise (WUN) dan
Colored Noise. In this research, the comparison of mother wavelet is performed
among Daubechies, Coiflet and Symlet in denoising process on speech. The
thresholding method that used in this denoising process is Soft Thresholding. The
threshold value is Time Adapted Threshold (TAT) that obtained by estimating the
power was used to generate the signal through Teager Energy Operator (TEO).
The kinds of tests that used for obtaining the best moher wavelet is Kruskal-
Wallis test and followed by Mann-Whitney test. The result shows that Db20,
Db30, Db40 and Coif5 mother wavelets are better than others to reduce WGN |
| first_indexed | 2024-03-13T23:00:59Z |
| format | Thesis |
| id | oai:generic.eprints.org:122702 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T23:00:59Z |
| publishDate | 2013 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:1227022016-03-04T08:42:44Z https://repository.ugm.ac.id/122702/ PERBANDINGAN MOTHER WAVELET DALAM PROSES DENOISING PADA SUARA , Rahmat Ramadhan , Dr. Agfianto Eko Putra, M. Si. ETD Wavelet Transform is a method that developed for analyzing the nonstationer signal. Wavelet Transform was used in denoising process on speech to enhance the quality of speech that courrupted by noise. The kinds of involved noises are White Gaussian Noise (WGN), White Uniform Noise (WUN) dan Colored Noise. In this research, the comparison of mother wavelet is performed among Daubechies, Coiflet and Symlet in denoising process on speech. The thresholding method that used in this denoising process is Soft Thresholding. The threshold value is Time Adapted Threshold (TAT) that obtained by estimating the power was used to generate the signal through Teager Energy Operator (TEO). The kinds of tests that used for obtaining the best moher wavelet is Kruskal- Wallis test and followed by Mann-Whitney test. The result shows that Db20, Db30, Db40 and Coif5 mother wavelets are better than others to reduce WGN [Yogyakarta] : Universitas Gadjah Mada 2013 Thesis NonPeerReviewed , Rahmat Ramadhan and , Dr. Agfianto Eko Putra, M. Si. (2013) PERBANDINGAN MOTHER WAVELET DALAM PROSES DENOISING PADA SUARA. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=62806 |
| spellingShingle | ETD , Rahmat Ramadhan , Dr. Agfianto Eko Putra, M. Si. PERBANDINGAN MOTHER WAVELET DALAM PROSES DENOISING PADA SUARA |
| title | PERBANDINGAN MOTHER WAVELET DALAM PROSES DENOISING PADA SUARA |
| title_full | PERBANDINGAN MOTHER WAVELET DALAM PROSES DENOISING PADA SUARA |
| title_fullStr | PERBANDINGAN MOTHER WAVELET DALAM PROSES DENOISING PADA SUARA |
| title_full_unstemmed | PERBANDINGAN MOTHER WAVELET DALAM PROSES DENOISING PADA SUARA |
| title_short | PERBANDINGAN MOTHER WAVELET DALAM PROSES DENOISING PADA SUARA |
| title_sort | perbandingan mother wavelet dalam proses denoising pada suara |
| topic | ETD |
| work_keys_str_mv | AT rahmatramadhan perbandinganmotherwaveletdalamprosesdenoisingpadasuara AT dragfiantoekoputramsi perbandinganmotherwaveletdalamprosesdenoisingpadasuara |