Institute of Information Theory and Automation

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Department of Adaptive Systems

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The Department of Adaptive Systems focuses predominantly on the design of decision-making systems, which modify their behavior according to the changing properties of their environment. This essential ability – adaptivity – enhances their efficiency. Decades of research have brought a number of conceptual, theoretical, algorithmic, software and application results. The applicability of adaptive systems is currently being extended toward complex scenarios by improving the classical adaptive systems and by developing their new versions.

The departmental “know-how” serves to resolve national as well as international research projects, running in collaboration with industry and government agencies. The interplay between theory and limited computing power is the common issue linking the various project domains. They include traffic control, management and control of technological systems, radiation protection, nuclear medicine, analysis of financial data, electronic democracy, etc. The increasing complexity of the problems addressed directs the main stream of the research toward decentralized control of large-scale systems and normative decision-making with multiple participants.

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Department detail

Our congratulations to Karel Macek, a member of the team of inventors, who recently has been granted several US patents...
The article Decentralized control and communication by L. Bakule is recognized by ScienceDirect as one of the Top 25...
An international workshop in conjunction withthe European Conference on Machine Learning and Principles and Practice of...
Czech Radiation Protection Society awarded prize for the best work of young authors in the field of protection against...
Ústav jaderného výzkumu Řež a.s. a Česká nukleární společnost ocenily disertační práci s názvem "Application of...
The 2011 Outstanding Statistical Application Award of American Statistical Association has been presented to Miroslav...
Miroslav Kárný and his co-authors A.Raftery (University of Washington) and P.Ettler (Compureg s.r.o.) were selected to...
Ing. Lubomír Bakule CSc.
Ing. Alkomiet Belal
Ing. Květoslav Belda Ph.D.
Ing. Milan Berka
Ing. Josef Böhm CSc.
Ing. Jindřich Bůcha CSc.
Ing. Kamil Dedecius Ph.D.
Dr. Siavash Fakhimi Derakhshan Ph.D.
Ing. Tatiana Valentine Guy Ph.D.
Mgr. Kateřina Henclová (Márová)
Ing. Jitka Homolová Ph.D.
RNDr. Ladislav Jirsa Ph.D.
Ing. Miroslav Kárný DrSc.
Ing. Václav Kůs Ph.D.
Ing. Petr Nedoma CSc.
Ing. Milan Papež
Ing. Lenka Pavelková Ph.D.
Ing. Petr Pecha CSc.
Anthony Paul Quinn
Prof. Oleksandr Rezunenko Ph.D.
RNDr. Vladimíra Sečkárová Ph.D.
Dominika Smolková
Ing. Vít Škvára
Doc. Ing. Václav Šmídl Ph.D.
Ing. Jakub Štěch
Ing. Ondřej Tichý Ph.D.
Ing. Lukáš Ulrych
Ing. Petr Zagalak CSc.
Duration: 2011 - 2014
The aim of this project is to create, verify and hand over to the industrial partner a prototype of a small urban traffic control system with an open interface. The control system is inspired by an existing macroscopic state-space model of an urban transportation network, that has been tested in real traffic conditions in winter 2010.
Duration: 2011 - 2013
The project deals with control algorithms directed at optimization of fuel consumption in vehicles from economical/ecological point of view. Bayesian methodology is used.
Duration: 2011 - 2014
The aim of this project is to explore new directions in diagnostics, control and parameter identification strategies of ac electric drives under critical operating conditions. Main attention will be paid to sensorless drive control and estimation in standstill and low speeds. We propose to explore suitability of methods from Bayesian identification and stochastic control in this area.
Duration: 2010 - 2013
Cílem projektu je zavedení moderního programového systému HARP a jeho asimilačního subsystému ASIM do praxe. Je určen pro podporu krizového řízení při zvládání následků mimořádných průmyslových nehod a havárií spojených s únikem radioaktivního znečistění do životního prostředí.
Duration: 2010 - 2011
Many engineering systems can be characterised as complex since they have a nonlinear behaviour incorporating a stochastic uncertainty. Urban traffic systems or traffic pollution propagation models are typical representatives of such complex systems. One of the most appropriate methods for modelling such systems is based on the application of Gaussian processes.