Jöres, NiklasNiklasJöresKaufmann, ChristophChristophKaufmannSchnelle, LeonaLeonaSchnelleCateriano Yáñez, CarlosCarlosCateriano YáñezPangalos, GeorgGeorgPangalosLichtenberg, GerwaldGerwaldLichtenberg2023-11-272023-11-272022https://publica.fraunhofer.de/handle/publica/45725610.5220/0011273100003274Large and highly complex systems can be found in various application areas. Modeling these systems requires appropriate representation of the underlying phenomena. Furthermore, due to the large dimensions efficient simulation and low memory requirements are needed for such models. Multilinear modeling is a promising approach to address these challenges. In this paper, we introduce a reduced canonical polyadic (CP) representation for implicit time-invariant multilinear (iMTI) models. This representation is capable of storing large models with very low memory requirements. This is particularly useful for efficient analyses of large systems with numerous inputs and states.enMultilinear SystemsTensor Decompositionconference paper