Research focus of Department of Theoretical Methods

• investigation of complex systems using characteristics known from the theory of chaos and fractals
• application of machine learning methods and self-organizing neural and other intelligent networks for the prediction and classification of time series and signals, especially in biomedicine
• causality detection from measured time series
• methods of nonlinear dynamics in signal processing and time series analysis; applications to complex manifestations of biological systems (ECG, EEG) – reconstruction of state portraits, noise reduction, modeling, prediction and classification

• research in applied statistics and machine learning methods for EEG processing and analysis
• basic and experimental research in the field of cognitive and computational neuroscience
• research on the use of brain-computer interface and virtual reality for neurorehabilitation of the paretic limb
• webpage of the research group is available here 

• research on linear and nonlinear regression models with complex covariance structure
• design of models and methods for analyzing measurement results, including methods for determining their uncertainty
• research on statistical and metrological intervals (statistical prediction intervals, confidence intervals, tolerance intervals and metrological coverage intervals)
• research on calibration models and methods for analyzing results of interlaboratory comparisons
• research on probability distributions determined by combining information from independent sources
• theoretical research on statistical parametric and non-parametric methods for biomedical and technical applications

Mgr. Michal Teplan, PhD.
Head of Research Group

• development of methods for the measurement and analysis of the biological effects of electromagnetic fields
• application of digital image analysis methods in optical microscopy (e.g. cell structures) and pattern recognition methods