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  • Generation of synthetic EEG signals for testing dynamic brain connectivity estimation methods [Elektronski vir]
    Šverko, Zoran ...
    : In this study, a method for generating synthetic signals of electroencephalographic (EEG) brain activity is presented. The generated signals are suitable for analysis and the development of methods ... for estimating direct functional connectivity such as Granger causality (GC) from the perspective of unveiling their dynamic capabilities. To make the synthetic signals as realistic as possible, they are generated from real EEG signals and based on a regression model obtained from them. A signal pair with a known causality relationship is generated from two input signals with high directional functional connectivity estimated by GC. Their autoregressive model is used to mix their unrelated parts according to the desired dynamic functional connectivity with values of GC in a range from 0 to the GC of source signals. As the source of generated signals are real signals and their model of mutual dependences, the generated signals have all realistic properties, including the realistic signal dependencies such as delays, and frequency relationships.
    Vir: Advances in signal processing and artificial intelligence [Elektronski vir] : proceedings of the 6th International Conference on Advances in Signal Processing and Artificial Intelligence : 17-19 April 2024 Funchal (Madeira Island), Portugal (Str. 103-107)
    Vrsta gradiva - prispevek na konferenci ; neleposlovje za odrasle
    Leto - 2024
    Jezik - angleški
    COBISS.SI-ID - 196331011

    Povezava(-e):

    https://sensorsportal.com/ASPAI_2024/ASPAI_2024_Proceedings.pdf

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