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### Forewords

The full version of the APRICOT library of the SMAC toolbox is freely available since September 2017. It can be used whatever the number of samples and explanatory variables, and with no limitation on the degree of the approximating functions.

• You are free to use any of the files of the APRICOT library of the SMAC toolbox for personal or academic use. The express permission of the authors is required for any commercial use.
• You can redistribute the APRICOT library of the SMAC toolbox and its manual without modification provided that it is for a non commercial purpose. Redistribution in any commercial form (CD-ROM, USB flash drive or any other media) is hereby forbidden, unless with the express written permission of the authors. Any of your software developments related to this download will be available under similar license conditions.
• Neither the authors nor ONERA accept any responsibility or liability with regard to this software that is licensed on an "as is" basis. There will be no duty on authors or ONERA to correct any errors or defects in the software.

### History

Current version of the APRICOT library: v1.2 released on 26 January 2022.
Older versions:

• v1.1 released on 29 March 2016.
• v1.0 released on 20 June 2014.

1. Download the GSS library (recommended) or the LFR toolbox (not maintained anymore).
3. Unzip both files in folders of your choice.
4. Add these folders to the Matlab path (including the subfolder subs of the APRICOT library).
5. Enjoy, and do not hesitate to contact Clément Roos (croos@onera.fr) in case of trouble or success!

### System requirements

The APRICOT library of the SMAC toolbox can be used on all platforms (Linux, Mac and Windows).

All routines run on Matlab 2010b or higher. They should run on older releases, but no validation has been performed. In particular, the numerical results provided to validate the routines have been computed with Matlab 2010b under Windows and can be slightly different with other configurations.

The GSS library and the LFR toolbox allow to create linear fractional representations of polynomial and rational approximating functions. One of these tools is thus strongly recommended, but all routines except lsapprox can be used without them. The Symbolic Math toolbox allows to create symbolic representations of polynomial and rational approximating functions, but all routines can be used without it. The Optimization toolbox is required by the routine qpapprox to compute a rational approximation using quadratic programming. The Robust Control toolbox is used by the routines qpapprox and tracker to check whether a rational function is nonsingular, but these routines can be used without it.

### Reference

The APRICOT library of the SMAC toolbox must be referenced when used in any published work:

 [1] C. Roos, G. Hardier and J-M. Biannic, "Polynomial and rational approximation with the APRICOT library of the SMAC toolbox", in Proceedings of the IEEE Multiconference on Systems and Control, Antibes, France, October 2014, pp. 1473-1478, available with the SMAC Toolbox at http://w3.onera.fr/smac/apricot.