Robust neural training and pruning algorithms for a class of nonlinear tracking control systems

This 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.

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Bibliographic Details
Main Author:	Ni, Jie
Other Authors:	Song Qing
Format:	Theses and Dissertations
Published:	2008
Subjects:	DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Online Access:	https://hdl.handle.net/10356/4973
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Institution:	Nanyang Technological University

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spelling	sg-ntu-dr.10356-49732023-07-04T17:22:37Z Robust neural training and pruning algorithms for a class of nonlinear tracking control systems Ni, Jie Song Qing School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems This 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. DOCTOR OF PHILOSOPHY (EEE) 2008-09-17T10:02:30Z 2008-09-17T10:02:30Z 2006 2006 Thesis Ni, J. (2006). Robust neural training and pruning algorithms for a class of nonlinear tracking control systems. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/4973 10.32657/10356/4973 Nanyang Technological University application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
topic	DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Ni, Jie Robust neural training and pruning algorithms for a class of nonlinear tracking control systems
description	This 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.
author2	Song Qing
author_facet	Song Qing Ni, Jie
format	Theses and Dissertations
author	Ni, Jie
author_sort	Ni, Jie
title	Robust neural training and pruning algorithms for a class of nonlinear tracking control systems
title_short	Robust neural training and pruning algorithms for a class of nonlinear tracking control systems
title_full	Robust neural training and pruning algorithms for a class of nonlinear tracking control systems
title_fullStr	Robust neural training and pruning algorithms for a class of nonlinear tracking control systems
title_full_unstemmed	Robust neural training and pruning algorithms for a class of nonlinear tracking control systems
title_sort	robust neural training and pruning algorithms for a class of nonlinear tracking control systems
publishDate	2008
url	https://hdl.handle.net/10356/4973
_version_	1772827409847943168

Robust neural training and pruning algorithms for a class of nonlinear tracking control systems

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