Study of User-Specified Parameters in Nonlinear Dynamics Modeling with Neural Networks

Research output: Chapter in Book/Report/Conference proceedingConference paper

1 Citation (Scopus)

Abstract

This work presents a study of the NN-NLSS method, an algorithm to model nonlinear dynamic systems that brings together the advantages of classic system identification on one hand, and some attractive properties of machine learning techniques on the other hand. This paper aims at gaining more insight on the approach, focusing in particular on the impact that different user-specified settings have on the algorithm performance. The analysis is performed by means of a simulation problem inspired by the challenging Wiener-Hammerstein benchmark example.
Original languageEnglish
Title of host publication11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing (ALCOSP), July 3-5, 2013 Caen, France
PublisherElsevier
Pages593-598
Number of pages6
ISBN (Print)978-3-902823-37-3
DOIs
Publication statusPublished - 3 Jul 2013
Event11th IFAC Workshop on Adaptation and Learning in Control and Signal Processing - Caen, France
Duration: 3 Jul 20137 Jul 2013

Publication series

NameIFAC Proceedings Volumes
PublisherElsevier
Number11
Volume45
ISSN (Electronic)1474-6670

Conference

Conference11th IFAC Workshop on Adaptation and Learning in Control and Signal Processing
Abbreviated titleIFAC PSYCO 2013
Country/TerritoryFrance
CityCaen
Period3/07/137/07/13

Keywords

  • Linear and nonlinear system identification

Fingerprint

Dive into the research topics of 'Study of User-Specified Parameters in Nonlinear Dynamics Modeling with Neural Networks'. Together they form a unique fingerprint.

Cite this