MOOSE2—A toolbox for least-costly application-oriented input design | Zendy

Mariette Annergren | Zendy; Christian A. Larsson | Zendy

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MOOSE2—A toolbox for least-costly application-oriented input design

Author(s) -

Mariette Annergren,

Christian A. Larsson

Publication year - 2016

Publication title -

softwarex

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.528

H-Index - 21

ISSN - 2352-7110

DOI - 10.1016/j.softx.2016.05.003

Subject(s) - toolbox , computer science , matlab , identification (biology) , parametric statistics , signal (programming language) , system identification , parametric model , spectral density , power (physics) , algorithm , mathematical optimization , data mining , programming language , mathematics , telecommunications , statistics , botany , physics , quantum mechanics , biology , measure (data warehouse)

MOOSE2 is a MATLAB®-based toolbox for solving least-costly application-oriented input design problems in system identification. MOOSE2 provides the spectrum of the input signal to be used in the identification experiment made to estimate a linear parametric model of the system. The objective is to find a spectrum that minimizes experiment cost while fulfilling constraints imposed in the experiment and on the obtained model. The constraints considered by MOOSE2 are: frequency or power constraints on the signal spectra in the experiment, and application or quality specifications on the obtained model

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