Head of the Department:
Jan Seidler

Deputy head of the Department:
Pavel Boček

Secretary:
Iva Marešová

phone: +420 266 052 466
www: http://www.utia.cas.cz/SI_
staff: people, Ph.D. students
List of publications, courses, projects

The Department concentrates on mathematical research in the following areas.

• Information in statistical experiments and optimal statistical decisions (estimation, testing, classification), with emphasis on maximum entropy, minimum divergence methods, and asymptotic theory.
• Robust statistical procedures and their applications in various statistical environments, including adaptivity and selforganization. Regression analysis.
• Statistical inference in random processes and random fields. Applications in stochastic optimization, change-point, optimum investment portfolios, and image and speech processing.
• Stochastic partial differential equations, particle systems.

Last events:

Prague Stochastics 2010

more info: http://simu0292.utia.cas.cz/pragstoch2010/

Continuing the series of international conferences on stochastics organized in Prague since 1956 the Department of Probability and Mathematical Statistics, Faculty of Mathematics and Physics, Charles University and the Department of Stochastic Informatics, Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic organize the Prague Stochastics 2010 which will be held from August 30 to September 3, 2010.

Workshop on Limit Theorems

The workshop will be held in UTIA from August 3 to August 6, 2009. The topics concern mainly the central limit theorem and invariance principles for sequences and arrays of dependent random variables. Many specialists of the field already confirmed their participation.

For more information see webpage: http://simu0292.utia.cas.cz/workshop09

We welcome you to attend the workshop.

Lucie Fajfrova (UTIA) and Dalibor Volny (Universite de Rouen, France), on behalf of the organisers.

Anotations

Blind Source Separation

Blind Source Separation consists of recovering original signals from their mixtures when the mixing process is unknown. In biomedicine, namely in MEG and EEG signal processing, one of the most popular algorithms nowadays is SOBI (Second Order Blind Identification).