Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/35735
Title: Studies on independent component analysis for watermarking and nonlinear blind source separation
Authors: Nguyen, Viet Thang
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2007
Source: Nguyen, V. T. (2007). Studies on independent component analysis for watermarking and nonlinear blind source separation. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: Independent Component Analysis (ICA) is one of the important methods in statistics and signal processing that deals with the data representation (transformation) problem. From the observed data, the goal of ICA is to estimate the mixing system and the underlying components that create those observed data. The most interesting thing is that ICA does it 'blindly' without prior knowledge of either the sources or the mixing system. Due to these attractive characteristics, ICA has been applied in many fields of science and engineering, for example, noise reduction, biomedicine, audio systems, telecommunication, and many others.
Description: 187 p.
URI: https://hdl.handle.net/10356/35735
DOI: 10.32657/10356/35735
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Theses

Files in This Item:
File Description SizeFormat 
SCE_THESES_21.pdf27.99 MBAdobe PDFThumbnail
View/Open

Page view(s) 50

289
Updated on Nov 26, 2020

Download(s) 50

109
Updated on Nov 26, 2020

Google ScholarTM

Check

Altmetric


Plumx

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