{"references": ["P. Benner, S. W. R. Werner, MORLAB -- A Model Order Reduction Framework in MATLAB and Octave, In A. M. Bigatti, J. Carette, J. H. Davenport, M. Joswig, and T. de Wolff, editors, Mathematical Software -- ICMS 2020, volume 12097 of Lecture Notes in Comput. Sci., pages 432--441. Springer International Publishing, Cham, 2020.", "P. Benner, S. W. R. Werner, Model reduction of descriptor systems with the MORLAB toolbox, IFAC-PapersOnLine 9th Vienna International Conference on Mathematical Modelling MATHMOD 2018, Vienna, Austria, 21--23 February 2018 51 (2) (2018) 547--552. https://doi.org/10.1016/j.ifacol.2018.03.092", "P. Benner, S. W. R. Werner, MORLAB - Modellreduktion in MATLAB, in: T. Meurer, F. Woittennek (Eds.), Tagungsband GMA-FA 1.30 'Modellierung, Identifikation und Simulation in der Automatisierungstechnik' und GMA-FA 1.40 'Theoretische Verfahren der Regelungstechnik', Workshop in Anif, Salzburg, 18.-22.09.2017, 2017, pp. 508--517. URL http://www.control.tf.uni-kiel.de/files/gma/2017/Tagungsband2017.pdf", "P. Benner, A MATLAB repository for model reduction based on spectral projection, in: 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, 2006, pp. 19--24. https://doi.org/10.1109/CACSD-CCA-ISIC.2006.4776618", "P. Benner, J. Saak, A semi-discretized heat transfer model for optimal cooling of steel profiles, in: P. Benner, V. Mehrmann, D. Sorensen (Eds.), Dimension Reduction of Large-Scale Systems, Vol. 45 of Lect. Notes Comput. Sci. Eng., Springer-Verlag, Berlin/Heidelberg, Germany, 2005, pp. 353--356. https://doi.org/10.1007/3-540-27909-1_19", "P. Benner, S. W. R. Werner, Balancing related model reduction with the MORLAB toolbox, Proc. Appl. Math. Mech. 18 (1) (2018) e201800083. https://doi.org/10.1002/pamm. 201800083"]}

The Software is provided as a MATLAB toolbox (.mltbx) file, an Octave package (.tar.gz) and a zip-archive. The toolbox-file needs a recent MATLAB version (R2018a or later) to install properly. For the Octave package, version 6.2.0 of Octave and above is recommended. The content of the zip-archive is equipped with all functions to also run on older releases. In order to get all functions registered properly, change to the installation folder and run the ml_addpath function. This will set the search path correctly for the current session. For citing the software, take a look into the CITATION file of the toolbox or call ml_citation.

The MORLAB, Model Order Reduction LABoratory, toolbox is a collection of MATLAB/Octave routines for model order reduction of dynamical systems. The implementation is based on spectral projection methods, like the matrix sign function and the matrix disk function, and on iterative low-rank solvers for large-scale sparse systems.