Basic Information

RNDr. Anna Krakovská, CSc.

Head of the Department of Theoretical Methods
Phone: +421-2-591045 36

Contact Address:

RNDr. Anna Krakovská, CSc.
Institute of Measurement Science
Slovak Academy of Sciences
Dúbravská cesta 9
841 04 Bratislava, Slovakia

More Information

1987 – MSc. in mathematics, Faculty of Mathematics and Physics, Comenius University in Bratislava and start of work at Institute of Measurement Science SAS
1993 – PhD. in bionics (thesis titled Nonlinear dynamics of selected biological systems)

On the present – head of the Department of Theoretical Methods

Current research interests

  • signal and time series analysis by methods of nonlinear dynamics; applications to complex physiological systems – reconstruction of multi-dimensional state portraits, noise reduction, modeling, prediction, study of causal relations
  • biological signals processing (ECG, EEG)
  • complexity estimation using measures known from the fractal theory and theory of chaos
  • Current research projects
    Principal investigator of the project: Causal analysis of measured signals and time series (2/0023/22, Sc. Grant Agency of Ministry of Education of Slovak Republic and Slovak Academy of Sciences, 2022-2025)

    All current projects

    SELECTED PUBLICATIONS, last 5 years

    • Krakovská A., Chvosteková M. (2023): Simple correlation dimension estimator and its use to detect causality. Chaos, Solitons & Fractals, 175, 113975 (full text)
    • Jakubík J., Phuong M., Chvosteková M., Krakovská A. (2023). Against the flow of time with multi-output models. Measurement Science Review, 23(4), 175-183 (full text)
    • Krakovská A., Rošt’áková Z., Chvosteková M., Maslíková J. (2023). Do Scalp EEG Measurements Allow Causal Inference? Proceedings of 14th International Conference on Measurement. pp. 92-95. IEEE. (full text)
    • Krakovská A., Pócoš Š., Mojžišová K., Bečková I., Gubáš J. X. (2022): State space reconstruction techniques and the accuracy of prediction. Communications in Nonlinear Science and Numerical Simulation, 111, p.106422 (full text)
    • Chvosteková M., Krakovská A. (2021): Letter to the editor of Heliyon re: Grassmann, G.“New considerations on the validity of the Wiener-Granger causality test”[Heliyon 6 (2020) e05208]. Heliyon, 7(9) (full text)
    • Krakovská A. (2021): Cross-Predictions in the Search for Effective Connectivity in Brain. Proceedings of 13th International Conference on Measurement. pp. 2-5. IEEE (full text)
    • Krakovská A. (2021): Cross-Predictions in the Search for Effective Connectivity in Brain. Proceedings of 13th International Conference on Measurement. pp. 2-5. IEEE
      (full text)
    • Krakovská H., Krakovská A. (2021): Problems of Estimating Fractal Dimension by Higuchi and DFA Methods for Signals That Are a Combination of Fractal and Oscillations. Proceedings of 13th International Conference on Measurement. pp. 84-87. IEEE (full text)
    • Chvosteková M., Jakubík J., Krakovská A. (2021): Granger causality on forward and reversed time series. Entropy, 23 (4), p. 409 (full text)
    • Krakovská A., Jakubík J. (2020): Implementation of two causal methods based on predictions in reconstructed state spaces. Physical Review E 102 (2), 022203 (full text)
    • Krakovská A. (2019): Correlation Dimension Detects Causal Links in Coupled Dynamical Systems. Entropy 21 (9), 818 (full text)
    • Krakovská A. (2019): Some Peculiarities of Causal Analysis of Coupled Chaotic Systems. Proceedings of 12th International Conference on Measurement. Smolenice, Slovakia, pp. 102-105. IEEE. (full text)
    • Krakovská A., Jakubík J., Chvosteková M., Coufal D., Jajcay N., Paluš M. (2018): Comparison of six methods for the detection of causality in a bivariate time series. Physical Review E, 97(4), 042207 (full text)
    • Paluš M., Krakovská A., Jakubík J., Chvosteková M.(2018): Causality, dynamical systems and the arrow of time. Chaos: An Interdisciplinary Journal of Nonlinear Science. 18, 28 (7): 075307 (full text)
    • Krakovská A. (2018): Power laws in stock market and fractal complexity of S&P500 and DAX. Proceedings of Papers, ITISE 2018, International Conference on Time Series and Forecasting, 19-21 September 2018, Granada (Spain), ISBN: 978-84-17293-57-4, 1113 – 1124 (full text)

    • Coufal D., Jakubík J., Jajcay N., Hlinka J., Krakovská A., Paluš M. (2017): Detection of coupling delay: a problem not yet solved, Chaos: An Interdisciplinary Journal of Nonlinear Science, 27(8), 083109 (abstract)
    • Krakovská, A. (2017): Predictability improvement as a tool to detect causality. In Measurement, 11th International Conference on, pp. 39-42 IEEE (full text)
    • Krakovská A., Škoviera R., Rosipal R. (2017): Spectral, complexity and interdependence measures of sleep EEG after ischemic stroke. In Measurement, 11th International Conference on, pp. 245-249 IEEE (full text)

    SELECTION FROM ALL PREVIOUS PUBLICATIONS here