Application of Ica in blind source separation

Application of Ica in blind source separation

The fundamental area in this project is Application of Independent Component Analysis (ICA) in Blind Source Separation. ICA is a tool for discovering structure and patterns in data by factoring a multidimensional data distribution into a product of onedimensional, statistically independent component...

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Main Author: That Mon Htwe.
Other Authors: Yang, Jun
Format: Theses and Dissertations
Published: 2008
Subjects:
DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Online Access:http://hdl.handle.net/10356/3575
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Institution: Nanyang Technological University
id sg-ntu-dr.10356-3575
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spelling sg-ntu-dr.10356-35752023-07-04T15:44:32Z Application of Ica in blind source separation That Mon Htwe. Yang, Jun School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing The fundamental area in this project is Application of Independent Component Analysis (ICA) in Blind Source Separation. ICA is a tool for discovering structure and patterns in data by factoring a multidimensional data distribution into a product of onedimensional, statistically independent component distributions. Traditional ICA methods, however, can be limited in the flexibility of their decompositions and in the modeling of component distributions. Master of Science (Signal Processing) 2008-09-17T09:32:46Z 2008-09-17T09:32:46Z 2005 2005 Thesis http://hdl.handle.net/10356/3575 Nanyang Technological University application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
topic DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
That Mon Htwe.
Application of Ica in blind source separation
description The fundamental area in this project is Application of Independent Component Analysis (ICA) in Blind Source Separation. ICA is a tool for discovering structure and patterns in data by factoring a multidimensional data distribution into a product of onedimensional, statistically independent component distributions. Traditional ICA methods, however, can be limited in the flexibility of their decompositions and in the modeling of component distributions.
author2 Yang, Jun
author_facet Yang, Jun
That Mon Htwe.
format Theses and Dissertations
author That Mon Htwe.
author_sort That Mon Htwe.
title Application of Ica in blind source separation
title_short Application of Ica in blind source separation
title_full Application of Ica in blind source separation
title_fullStr Application of Ica in blind source separation
title_full_unstemmed Application of Ica in blind source separation
title_sort application of ica in blind source separation
publishDate 2008
url http://hdl.handle.net/10356/3575
_version_ 1772826398905335808

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