V. Peterka, J. Krýže, and A. Fořtová. Numerical solution of Wiener-Hopf equation in statistical identification of linear dynamic systems. Kybernetika, 2:331-346, 1966. Download.
| Nadpis | Date&Time |
|---|---|
| Analysis of DNA Mixtures with Artefacts | 18.06.2013 - 14:00 |
| Estimation and tests under L-moment condition models and applications to radar detection | 08.04.2013 - 14:00 |
| Accumulation Points of the Iterative Proportional Fitting Procedure | 25.02.2013 - 14:00 |
| Nonparametric Estimation of Phylogenetic Tree Distributions | 11.09.2012 - 11:00 |
| Measure concentration minischool | 21.08.2012 - 09:00 |
| Maximizing the information divergence | 01.10.2010 - 14:30 |
Ve dnech 5.-7.června 2012 v Selském dvoře v Biskoupkách u Zbiroha proběhl letošní ročník tradičního výjezdního semináře "Pravděpodobnostní a jiné metody rozhodování".
Akademická rada Akademie věd ČR, na základě návrhu poroty pro udělování Prémií Otto Wichterleho mladým vědeckým pracovníkům v AV ČR, udělila Prémii Otto Wichterleho v roce 2012
PhDr. Jozefu Baruníkovi, Ph.D.
z Ústavu teorie informace a automatizace.
One of the key objectives of any rolling mill control system is to keep the thickness of the processed material within the prescribed tolerance band, which can be as low as +-10 micrometers for thin strips. Failure to comply with the tolerances results in losses which, according to experts estimate, might go up to 10% of the profit for poorly equipped rolling mills. Unfortunately, no practical direct measurement of the gauge within the rolling gap is possible. Strip thickness can be measured 50--100cm after the rolling gap with a high transport delay (20--120 samples).
A state space model is frequently used for a description of real systems. Usually, some state variables are hidden and cannot be measured directly and some model parameters are unknown. Then, the need for learning, i.e., the state filtering and parameter estimation, arises. Probabilistic models provide a suitable description of the always uncertain reality and call for such approaches as Bayesian learning. Uncertainties are standardly modelled by the Gaussian distribution. This leads to Kalman-filter-based algorithms.
This research project aims at optimization of fuel consumption both from the economical and ecological points of view.
| 4.2. | Miroslav Kárný |
| 4.3. | Ondřej Tichý |
| 8.4. | Václav Šmídl |
| 6.5. | Vladimíra Sečkárová |
| 3.6. | Ladislav Jirsa |
| 2.9. | Petr Pecha |