Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/19571
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

Files in This Item:
File Description SizeFormat 
EEE_THESES_12.pdf
  Restricted Access
10.52 MBAdobe PDFView/Open

Google ScholarTM

Check

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