Non-parametric identification in dynamic networks

Arne Dankers, Paul Van den Hof

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

3 Citations (Scopus)
2 Downloads (Pure)


In this paper we present a non-parametric approach to identification in networks. The main advantage of a non-parametric approach is that consistent estimates can be obtained with very little prior knowledge about the system. This is a particularly important consideration for a network identification problem which can easily become very complex with high order dynamics and many inputs. We consider a very general framework for dynamic networks that includes measured variables, external excitation variables, process noise, and sensor noise.
Original languageEnglish
Title of host publication54th IEEE Conference on Decision and Control (CDC 2015), 15-18 December 2015, Osaka, Japan
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)978-1-4799-7885-4
ISBN (Print)978-1-4799-7884-7
Publication statusPublished - 2015
Event54th IEEE Conference on Decision and Control (CDC 2015) - "Osaka International Convention Center", Osaka, Japan
Duration: 15 Dec 201518 Dec 2015
Conference number: 54


Conference54th IEEE Conference on Decision and Control (CDC 2015)
Abbreviated titleCDC 2015
Internet address


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