The University of Southampton
University of Southampton Institutional Repository

A learning approach to identification of nonlinear physiological systems using wiener models

A learning approach to identification of nonlinear physiological systems using wiener models
A learning approach to identification of nonlinear physiological systems using wiener models
472-476
Springer
Jing, X.J.
2069201e-c435-4a3a-9c5a-e9b86855d3b0
Angarita, N.
e2299cca-4ec3-4123-8bd8-25d5c02125dd
Simpson, D.M.
53674880-f381-4cc9-8505-6a97eeac3c2a
Allen, R.
956a918f-278c-48ef-8e19-65aa463f199a
Newland, P.L.
7a018c0e-37ba-40f5-bbf6-49ab0f299dbb
Jing, X.J.
2069201e-c435-4a3a-9c5a-e9b86855d3b0
Angarita, N.
e2299cca-4ec3-4123-8bd8-25d5c02125dd
Simpson, D.M.
53674880-f381-4cc9-8505-6a97eeac3c2a
Allen, R.
956a918f-278c-48ef-8e19-65aa463f199a
Newland, P.L.
7a018c0e-37ba-40f5-bbf6-49ab0f299dbb

Jing, X.J., Angarita, N., Simpson, D.M., Allen, R. and Newland, P.L. (2011) A learning approach to identification of nonlinear physiological systems using wiener models. In Proceedings of Biosignals 2011 International Conference on Bio-inspired Systems and Signal Processing. Springer. pp. 472-476 .

Record type: Conference or Workshop Item (Paper)

This record has no associated files available for download.

More information

Published date: January 2011
Additional Information: CD-ROM
Venue - Dates: Biosignals 2011 International Conference on Bio-inspired Systems and Signal Processing, Rome, Italy, 2011-01-26 - 2011-01-29

Identifiers

Local EPrints ID: 192065
URI: http://eprints.soton.ac.uk/id/eprint/192065
PURE UUID: b0e936e9-6c0d-4b23-9882-0df76338d94e
ORCID for D.M. Simpson: ORCID iD orcid.org/0000-0001-9072-5088
ORCID for P.L. Newland: ORCID iD orcid.org/0000-0003-4124-8507

Catalogue record

Date deposited: 29 Jun 2011 13:33
Last modified: 09 Jan 2022 03:10

Export record

Contributors

Author: X.J. Jing
Author: N. Angarita
Author: D.M. Simpson ORCID iD
Author: R. Allen
Author: P.L. Newland ORCID iD

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 http://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.

×