Pruned hierarchical local model networks for nonlinear system identification: neuro-fuzzy local model network-based nonlinear system identification using maximum likelihood partitioned hierarchical model trees and backward elimination pruning for structure optimisation

Mathematical models form the basis of application in a multitude of processes and disciplines. With there being a recent and general trend of increased system complexity through added dimensionality and new innovations in technology, conventional characterisation methods fall short in many key areas...

Full description

Bibliographic Details

Main Author:	Aitshaam Shahzad
Format:	Default Thesis
Published:	2020
Subjects:	Other engineering not elsewhere classified System Identification Nonlinear Systems Neuro-Fuzzy Models Local Model Networks Tree-Structured Networks Time Series Analysis Information Theory Static and Dynamic Systems Engineering not elsewhere classified
Online Access:	https://dx.doi.org/10.26174/thesis.lboro.13028231.v1
Tags:	Add Tag No Tags, Be the first to tag this record!