Publications DRI Group

Gosea, I. V.; Zhang, Q.; Antoulas, A. C.: Preserving the DAE Structure in the Loewner Model Reduction and Identification Framework. Advances in Computational Mathematics 46, 3 (2020)

Antoulas, A. C.; Gosea, I. V.; Heinkenschloss, M.: Data-Driven Model Reduction for a Class of Semi-Explicit DAEs Using the Loewner Framework. In: Progress in Differential-Algebraic Equations II, pp. 185 - 210 (Eds. Reis, T.; Grundel, S.; Schöps, S.). Springer, Cham (2020)

Gosea, I. V.; Pontes Duff, I.; Benner, P.; Antoulas, A. C.: Model Order Reduction of Switched Linear Systems with Constrained Switching. In: IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018, pp. 41 - 53 (Eds. Fehr, J.; Haasdonk, B.) (2020)

Gosea, I. V.; Petreczky, M.; Leth, J.; Wisniewski, R.; Antoulas, A. C.: Model Reduction of Linear Hybrid Systems. In: 2020 59th IEEE Conference on Decision and Control (CDC), 9303918, pp. 110 - 117. 59th IEEE Conference on Decision and Control (CDC), Jeju Island, Korea (South), December 14, 2020 - December 18, 2020. IEEE (2020)

Antoulas, A. C.; Gosea, I. V.; Heinkenschloss, M.: Reduction of Systems with Polynomial Nonlinearities in the Loewner Framework. In XXI Householder Symposium on Numerical Linear Algebra: Book of Abstracts, pp. 96 - 98. XXI Householder Symposium on Numerical Linear Algebra, Selva di Fasano, Italy, June 14, 2020 - June 19, 2020. (2020)

Gosea, I. V.; Petreczky, M.; Fiter, C.; Antoulas, A. C.: Balanced Truncation for Linear Switched Systems. In XXI Householder Symposium on Numerical Linear Algebra: Book of Abstracts, pp. 196 - 198. XXI Householder Symposium on Numerical Linear Algebra, Selva di Fasano, Italy, June 14, 2020 - June 19, 2020. (2020)

Gosea, I. V.; Antoulas, A. C.: Learning block-oriented nonlinear models of dynamical systems from data. Workshop on Algorithms for Dimension and Complexity Reduction, ICERM, Providence, RI, USA (2020)

Gosea, I. V.; Antoulas, A. C.: Rational approximation of the absolute value function from measurements: a numerical study of recent methods. (2020)