Evidence of Chaos in EEG Signals: An Application to BCI

DOI10.1007/978-3-319-30340-6_25zbMath1359.92065OpenAlexW2502380527MaRDI QIDQ2975875

K. Srikanta Murthy, Snehanshu Saha, Kusuma Mohanchandra

Publication date: 12 April 2017

Published in: Advances in Chaos Theory and Intelligent Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-30340-6_25

zbMATH Keywords

chaoshigher-order spectraLyapunov exponentsfractal dimensionHurst exponentcorrelation dimensionEEGsample entropyLempel-Ziv complexityHopf bifurcation theoremapproximate entropy

Mathematics Subject Classification ID

Biomedical imaging and signal processing (92C55) Bifurcation theory for ordinary differential equations (34C23) Strange attractors, chaotic dynamics of systems with hyperbolic behavior (37D45)

Cites Work

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• Chaos modeling and control systems design
• A practical method for calculating largest Lyapunov exponents from small data sets
• Approximate entropy as a measure of system complexity.

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