Article

The Advanced Complexity Analysis of Electroencephalography (EEG) Data Using Tsallis Entropy

2024-09-05

Abstract excerpt

This paper introduces a novel application of Tsallis entropy for complexity analysis in electroencephalography (EEG) data. Tsallis entropy, a generalization of Shannon entropy, is employed to uncover hidden structures and distinguish varying complexity levels in EEG signals. By leveraging this framework on publicly available EEG datasets, the study demonstrates that Tsallis entropy is highly effective in categoriz...

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Literature Corpus work: 0758ff6a-1f8a-5389-9bf3-4f8f943dace2
DOI: 10.1590/scielopreprints.9622

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