Comparative Study Of Time-Frequency Analysis Approaches With Application To Economic Indicators. - Jiri Blumenstein; Jitka Pomenková; Roman Marsálek (ECMS, 2012)

The Modified Empirical Mode Decomposition Method For Analysing The Cyclical Behavior Of Time Series. - Vladimir Sebesta; Roman Marsálek; Jitka Pomenková (ECMS, 2013)

Wireless device authentication through transmitter imperfections - measurement and classification. - Martin Pospísil; Roman Marsálek; Jitka Pomenková (PIMRC, 2013)

Learning of a robusted nearest neighbor classifier using multiple training data. - Tobias Malach; Jitka Pomenková (IWSSIP, 2016)

Optimization of time-frequency curve description via kernel smoothing. - Jitka Pomenková; Eva Klejmova (IWSSIP, 2016)

Combination Of Time-Frequency Representations For Background Noise Suppression. - Eva Klejmova; Jitka Pomenková; Jiri Blumenstein (ECMS, 2017)

Evaluation of background noise for significance level identification. - Jitka Pomenková; Eva Klejmova; Tobias Malach (IWSSIP, 2017)

Segmentation Based Testing of Co-Movement Significance. - Eva Klejmova; Tobias Malach; Jitka Pomenková (IWSSIP, 2018)

Optimal face templates: the next step in surveillance face recognition. - Tobias Malach; Jitka Pomenková (Pattern Anal. Appl., 2020)

Correction to: Optimal face templates: the next step in surveillance face recognition. - Tobias Malach; Jitka Pomenková (Pattern Anal. Appl., 2020)

Co-movement selective detection filter to identify time series co-movement indicator or to filter out symmetric economic shocks. - Jitka Pomenková; Eva Klejmova (Digit. Signal Process., 2021)

Text Data Pre-Processing for Time-series Modelling. - Jitka Pomenková; Petr Koráb; David Strba (RADIOELEKTRONIKA, 2023)

Optimized Classifier Learning for Face Recognition Performance Boost in Security and Surveillance Applications. - Jitka Pomenková; Tobias Malach (Sensors, 2023)

Arabica: A Python package for exploratory analysis of text data. - Petr Koráb; Jitka Pomenková (J. Open Source Softw., 2024)