dc.contributor.authorNi, Jieen_US
dc.date.accessioned2008-09-17T10:02:30Z
dc.date.accessioned2017-07-23T08:32:07Z
dc.date.available2008-09-17T10:02:30Z
dc.date.available2017-07-23T08:32:07Z
dc.date.copyright2006en_US
dc.date.issued2006
dc.identifier.citationNi, J. (2006). Robust neural training and pruning algorithms for a class of nonlinear tracking control systems. Doctoral thesis, Nanyang Technological University, Singapore.
dc.identifier.urihttp://hdl.handle.net/10356/4973
dc.description.abstractThis thesis focuses on developing robust online training and pruning algorithms for a class of neural network tracking control systems. In particular, a complete convergence analysis is presented for all the algorithms with different learning schemes, respectively.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
dc.titleRobust neural training and pruning algorithms for a class of nonlinear tracking control systemsen_US
dc.typeThesisen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.contributor.supervisorSong Qingen_US
dc.description.degreeDOCTOR OF PHILOSOPHY (EEE)en_US
dc.identifier.doihttps://doi.org/10.32657/10356/4973


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