Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/35735
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dc.contributor.authorNguyen, Viet Thangen
dc.date.accessioned2010-04-23T01:31:33Zen
dc.date.available2010-04-23T01:31:33Zen
dc.date.copyright2007en
dc.date.issued2007en
dc.identifier.citationNguyen, V. T. (2007). Studies on independent component analysis for watermarking and nonlinear blind source separation. Doctoral thesis, Nanyang Technological University, Singapore.en
dc.identifier.urihttps://hdl.handle.net/10356/35735en
dc.description187 p.en
dc.description.abstractIndependent 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.en
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processingen
dc.titleStudies on independent component analysis for watermarking and nonlinear blind source separationen
dc.typeThesisen
dc.contributor.supervisorJagdish Chandra Patraen
dc.contributor.schoolSchool of Computer Engineeringen
dc.description.degreeDOCTOR OF PHILOSOPHY (SCE)en
dc.identifier.doi10.32657/10356/35735en
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