Segmentation of heart sound signals and denoising of magnetic resonance images using wavelets
71 p.
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2011
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sg-ntu-dr.10356-469252023-07-04T15:49:23Z Segmentation of heart sound signals and denoising of magnetic resonance images using wavelets Seramani Sankar. Chan Kap Luk School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing 71 p. Wavelet is one of the most fascinating developments in mathematics and signal processing. Daubechies developed the first continuous compactly supported wavelets leading to the development of wavelets to signal and image processing. In this dissertation application of wavelets to heart sound signal segmentation and denoising of magnetic resonance images are investigated. Master of Science (Signal Processing) 2011-12-27T05:45:35Z 2011-12-27T05:45:35Z 2011 Thesis http://hdl.handle.net/10356/46925 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Seramani Sankar. Segmentation of heart sound signals and denoising of magnetic resonance images using wavelets |
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71 p. |
author2 |
Chan Kap Luk |
author_facet |
Chan Kap Luk Seramani Sankar. |
format |
Theses and Dissertations |
author |
Seramani Sankar. |
author_sort |
Seramani Sankar. |
title |
Segmentation of heart sound signals and denoising of magnetic resonance images using wavelets |
title_short |
Segmentation of heart sound signals and denoising of magnetic resonance images using wavelets |
title_full |
Segmentation of heart sound signals and denoising of magnetic resonance images using wavelets |
title_fullStr |
Segmentation of heart sound signals and denoising of magnetic resonance images using wavelets |
title_full_unstemmed |
Segmentation of heart sound signals and denoising of magnetic resonance images using wavelets |
title_sort |
segmentation of heart sound signals and denoising of magnetic resonance images using wavelets |
publishDate |
2011 |
url |
http://hdl.handle.net/10356/46925 |
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1772827136802947072 |