Some Aspects of Nonlinear Black-Box Modeling in System Identification
1996 (English)In: Proceedings of the 1996 Conference on Communications, Computing, Control and Signal Processing, Kluwer Academic Publishers, 1996, 431-440 p.Conference paper (Refereed)
The key problem in system identification is to find a suitable model structure, within which a good model is to be found. Fitting a model within a given structure (parameter estimation) is in most cases a lesser problem. A basic rule in estimation is not to estimate what you already know. In other words, one should utilize prior knowledge and physical insight about the system when selecting the model structure. It is customary to distinguish between three levels of prior knowledge, which have been color-coded as follows.
Place, publisher, year, edition, pages
Kluwer Academic Publishers, 1996. 431-440 p.
System identification, Parameter estimation, Nonlinear, Black-box modeling
IdentifiersURN: urn:nbn:se:liu:diva-93713DOI: 10.1007/978-1-4615-6281-8_26ISBN: 978-1-4613-7883-9OAI: oai:DiVA.org:liu-93713DiVA: diva2:629075
1996 Conference on Communications, Computing, Control and Signal Processing, Stanford, CA, USA, June, 1996