An integrated toolbox for linear and non-linear models

Autor:	Ljung, Lennart, Zhang, Qinghua, Lindskog, Peter, Singh, Rajiv
Přispěvatelé:	Information Coding - Department of Electrical Engineering [Linköping] (ISY/ICG), Linköping University (LIU), SIgnals and SYstems in PHysiology & Engineering (SISYPHE), Inria Paris-Rocquencourt, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), NIRA Dynamics AB, Brett Ninness and Håkan Hjalmarsson
Jazyk:	angličtina
Rok vydání:	2006
Předmět:	[INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering nonlinear system identification neural networks nonlinear models
Zdroj:	14th IFAC Symposium on System Identification (SYSID) 14th IFAC Symposium on System Identification (SYSID), Mar 2006, Newcastle, Australia. pp.931-936, ⟨10.3182/20060329-3-AU-2901.00148⟩
DOI:	10.3182/20060329-3-AU-2901.00148⟩
Popis:	International audience; The paper describes additions to the Matlab System Identification Toolbox, that handle also the estimation of nonlinear models. Both structured grey-box models and general, flexible black-box models are covered. The idea is that the look and feel of the syntax, and the graphical user interface should be as close as possible to the linear case.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::8225254eb53e907c4596353773f6c53a https://inria.hal.science/hal-00854864 Zobrazit plný text záznamu