A Mathematica Toolbox for Signals, Systems and Identification System Identification
Paper i proceeding, 2012

In this contribution we provide a status report for the Mathematica toolbox that is described in Sjöberg 2008. The toolbox covers a comprehensive set of functions for handling deterministic and stochastic signals and models. On top of this the toolbox provides signal processing and system identification methods ranging from non-parametric to parametric, and from linear models to a wide class of non-linear models. Algorithms are tailored to be able to efficiently handle large scale data sets and models as well as symbolic computations. This allows theory to be handled alongside practice, implying that the toolbox provides an environment suitable both for education and data processing. In regards to system identification, one of the novel features is graphical support for building block-based nonlinear models. Another novel feature is that modeling errors can be propagated through applications.

system identification

software tools

Författare

Håkan Hjalmarsson

Kungliga Tekniska Högskolan (KTH)

Jonas Sjöberg

Chalmers, Signaler och system, System- och reglerteknik, Mekatronik

IFAC Proceedings Volumes (IFAC-PapersOnline)

14746670 (ISSN)

Vol. 16 1 1541-1546

Styrkeområden

Energi

Ämneskategorier

Reglerteknik

Signalbehandling

DOI

10.3182/20120711-3-BE-2027.00273

ISBN

9783902823069