Abstract
Multiaffine hybrid automata (MHA) represent a powerful formalism to model complex dynamical systems. This formalism is particularly suited for the representation of biological systems which often exhibit highly non-linear behavior. In this paper, we consider the problem of parameter identification for MHA. We present an abstraction of MHA based on linear hybrid automata, which can be analyzed by the SpaceEx model checker. This abstraction enables a precise handling of time-dependent properties. We demonstrate the potential of our approach on a model of a genetic regulatory network and a myocyte model.
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Acknowledgments
This work was partly supported by the European Research Council (ERC) under grant 267989 (QUAREM), by the Austrian Science Fund (FWF) under grants S11402-N23, S11405-N23 and S11412-N23 (RiSE/SHiNE) and Z211-N23 (Wittgenstein Award), and by the German Research Foundation (DFG) as part of the Transregional Collaborative Research Center “Automatic Verification and Analysis of Complex Systems” (SFB/TR 14 AVACS, http://www.avacs.org/).
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Bogomolov, S., Schilling, C., Bartocci, E., Batt, G., Kong, H., Grosu, R. (2015). Abstraction-Based Parameter Synthesis for Multiaffine Systems. In: Piterman, N. (eds) Hardware and Software: Verification and Testing. HVC 2015. Lecture Notes in Computer Science(), vol 9434. Springer, Cham. https://doi.org/10.1007/978-3-319-26287-1_2
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DOI: https://doi.org/10.1007/978-3-319-26287-1_2
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