Software package for mosaic-Hankel structured low-rank approximation

Konstantin Usevich (1) , Ivan Markovsky (2)

1 CRAN - Centre de Recherche en Automatique de Nancy
2 ELEC - Department of Fundamental Electricity and Instrumentation

This paper presents the SLRA package (http://slra.github.io)-C software with interface to MATLAB, Octave, and R for solving low-rank approximation problems with the following features: mosaic Hankel structured approximating matrix, weighted 2-norm approximation criterion, and fixed and missing elements in the approximating matrix. The package has applications in system identification , machine learning, and computer algebra. The paper gives an overview of the features of the package, including the wrapper functions for system identification (IDENT package) and approximate greatest common divisor (AGCD) computations. The addendum to the paper, available from http: //homepages.vub.ac.be/˜imarkovs/slra-demo, includes examples that demonstrate the usage, versatility, and efficiency of the software.

Mots clés: System identification; low-rank approximation; mosaic Hankel matrix; missing data; approximate greatest common factor; software

Domaines: Traitement du signal et de l'image [eess.SP]; Automatique

Konstantin Usevich, Ivan Markovsky. Software package for mosaic-Hankel structured low-rank approximation. 58th IEEE Conference on Decision and Control, CDC 2019, Dec 2019, Nice, France. pp.7165-7170. ⟨hal-02402026⟩