Investigation of Stationarity for Graph Time Series Data Sets

Güneyi, Eylem Tuğçe
Vural, Elif
Graphs permit the analysis of the relationships in complex data sets effectively. Stationarity is a feature that facilitates the analysis and processing of random time signals. Since graphs have an irregular structure, the definition of classical stationarity does not apply to graphs. In this study, we study how stationarity is defined for graph random processes and examine the validity of the stationarity assumption with experiments on synthetic and real data sets.
2020 28th Signal Processing and Communications Applications Conference (SIU)


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Citation Formats
E. T. Güneyi and E. Vural, “Investigation of Stationarity for Graph Time Series Data Sets,” presented at the 2020 28th Signal Processing and Communications Applications Conference (SIU), 2021, Accessed: 00, 2021. [Online]. Available: