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|Title:||Transient improvement via neural and switching control||Authors:||Xu, Fang||Keywords:||DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering||Issue Date:||1998||Abstract:||This thesis contains three main results. The first result deals with an in-depth discussion of the radial basis function network where a training algorithm is proposed and the convergence of the RBF network is analyzed. The proof of convergence is based on the finite cover theory and the geometric growth criterion, which is the basis of the RBF network training algorithm.||URI:||http://hdl.handle.net/10356/19571||Rights:||NANYANG TECHNOLOGICAL UNIVERSITY||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Theses|
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