Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Csáji, Balázs Cs."'
Sign-Perturbed Sums (SPS) is a system identification method that constructs confidence regions for the unknown system parameters. In this paper, we study SPS for ARX systems, and establish that the confidence regions are guaranteed to include the tru
Externí odkaz:
http://arxiv.org/abs/2402.11528
Autor:
Szentpéteri, Szabolcs, Kis, Krisztián B., Egri, Péter, Sanges, Carmen, Danhof, Sophia, Mestermann, Katrin, Hudecek, Michael, Velázquez, Sergio Navarro, Juan, Manel, Csáji, Balázs Cs.
Publikováno v:
In Procedia CIRP 2024 125:154-159
Publikováno v:
IEEE Transactions on Signal Processing, Volume 63, Issue 1, 2015, pp. 169-181
We propose a new system identification method, called Sign-Perturbed Sums (SPS), for constructing non-asymptotic confidence regions under mild statistical assumptions. SPS is introduced for linear regression models, including but not limited to FIR s
Externí odkaz:
http://arxiv.org/abs/1807.08216
Autor:
Monostori, László, Csáji, Balázs Cs., Egri, Péter, Kis, Krisztián B., Váncza, József, Ochs, Jelena, Jung, Sven, König, Niels, Pieske, Simon, Wein, Stephan, Schmitt, Robert, Brecher, Christian
Publikováno v:
In CIRP Journal of Manufacturing Science and Technology August 2021 34:84-94
Autor:
Monostori, László, Csáji, Balázs Cs., Egri, Péter, Kis, Krisztián B., Váncza, József, Ochs, Jelena, Jung, Sven, König, Niels, Pieske, Simon, Wein, Stephan, Schmitt, Robert, Brecher, Christian
Publikováno v:
In CIRP Journal of Manufacturing Science and Technology May 2021 33:369-379
We propose a generalization of the recently developed system identification method called Sign-Perturbed Sums (SPS). The proposed construction is based on the instrumental variables estimate and, unlike the original SPS, it can construct non-asymptot
Externí odkaz:
http://arxiv.org/abs/1509.04774
Autor:
Egri, Péter, Csáji, Balázs Cs., Kis, Krisztián B., Monostori, László, Váncza, József, Ochs, Jelena, Jung, Sven, König, Niels, Schmitt, Robert, Brecher, Christian, Pieske, Simon, Wein, Stephan
Publikováno v:
In Procedia CIRP 2020 88:600-605
Publikováno v:
In IFAC PapersOnLine 2020 53(2):7142-7147
Autor:
Csáji, Balázs Cs., Browet, Arnaud, Traag, V. A., Delvenne, Jean-Charles, Huens, Etienne, Van Dooren, Paul, Smoreda, Zbigniew, Blondel, Vincent D.
Publikováno v:
Physica A 392(6), pp. 1459-1473 (2013)
Mobile phone datasets allow for the analysis of human behavior on an unprecedented scale. The social network, temporal dynamics and mobile behavior of mobile phone users have often been analyzed independently from each other using mobile phone datase
Externí odkaz:
http://arxiv.org/abs/1211.6014
Publikováno v:
In IFAC PapersOnLine July 2017 50(1):2744-2749