KEYNOTE TALKS

Selected time series and their spectra in geosciences

dr Maciej J. Mendecki

Natural processes often generate time series data across various phenomena. One common type of time series, which can be effectively analyzed through spectral techniques, is ground motion evoked by both natural and anthropogenic events. The characteristics of these events may vary, encompassing waveforms produced by seismic events or ambient seismic noise. In seismology, spectral analysis can be used to filter waveforms for clear signals, identify dominant frequencies that reflect focal characteristics, and even recognize near-surface site effects influenced by local geology. Beyond seismology, time series analysis has applications across other areas of geoscience, where patterns may be less immediately apparent. 

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Integrated Sensing and Communications (ISAC): Goals and Examples

prof. dr hab. inż Tomasz P. Zieliński

Tomasz Piotr Zieliński received the M.Sc. and D.Sc. degrees in electronics and electrical engineering from the AGH University of Science and Technology (AGH-UST), Krakow, Poland, in 1982 and 1996, respectively, and the Ph.D. degree in electrical engineering from the Bulgarian Academy of Sciences, Sofia, Bulgaria, in 1988.,Since 2006, he has been a Full Professor with the Department of Telecommunications, AGH-UST. In 2021, he authored the textbook Starting Digital Signal Processing in Telecommunication Engineering. A Laboratory-Based Course published by Springer Nature. His research interests include advanced digital signal processing in telecommunication, biomedical and smart power delivery systems, particularly time-frequency, and time-scale signal analysis.

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