The University of Southampton
University of Southampton Institutional Repository

A tunable radial basis function model for nonlinear system identification using particle swarm optimisation

A tunable radial basis function model for nonlinear system identification using particle swarm optimisation
A tunable radial basis function model for nonlinear system identification using particle swarm optimisation
6762-6767
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Hong, Xia
e6551bb3-fbc0-4990-935e-43b706d8c679
Luk, Bing L.
7f992721-74f4-4a2d-b990-afcece627189
Harris, Chris J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Hong, Xia
e6551bb3-fbc0-4990-935e-43b706d8c679
Luk, Bing L.
7f992721-74f4-4a2d-b990-afcece627189
Harris, Chris J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a

Chen, Sheng, Hong, Xia, Luk, Bing L. and Harris, Chris J. (2009) A tunable radial basis function model for nonlinear system identification using particle swarm optimisation. Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference, China. 16 - 18 Dec 2009. pp. 6762-6767.

Record type: Conference or Workshop Item (Paper)
Text cdc09-16M.pdf - Version of Record
Download (155kB)
Text cdc09-16.pdf - Version of Record
Download (525kB)

More information

Published date: December 2009
Additional Information: Event Dates: December 16-18, 2009
Venue - Dates: Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference, China, 2009-12-16 - 2009-12-18
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 268287
URI: https://eprints.soton.ac.uk/id/eprint/268287
PURE UUID: 598304e9-7d2a-446d-bcd7-a5c7a279b8a1

Catalogue record

Date deposited: 30 Nov 2009 17:11
Last modified: 02 Feb 2018 17:34

Export record

Contributors

Author: Sheng Chen
Author: Xia Hong
Author: Bing L. Luk
Author: Chris J. Harris

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×