Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/4156
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dc.contributor.authorChoo, Chun Keong.en_US
dc.date.accessioned2008-09-17T09:45:41Z-
dc.date.available2008-09-17T09:45:41Z-
dc.date.copyright2003en_US
dc.date.issued2003-
dc.identifier.urihttp://hdl.handle.net/10356/4156-
dc.description.abstractThis thesis looks into the methodologies of implementing hybrid neural network for data classification application. Among the vast varieties of Artificial Neural Network (ANN) architectures, each has its own unique capabilities. By proper combination of information from various specialised neural networks of different paradigms.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems-
dc.titleData classification using hybrid SOM-RBF architectureen_US
dc.typeThesisen_US
dc.contributor.supervisorSuganthan, Ponnuthurai Nagaratnamen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Computer Control and Automation)en_US
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