TY  - JOUR
A1  - Schinkel, Stefan
A1  - Marwan, Norbert
A1  - Dimigen, Olaf
A1  - Kurths, Jürgen
T1  - Confidence bounds of recurrence-based complexity measures
N2  - In the recent past, recurrence quantification analysis (RQA) has gained an increasing interest in various research areas. The complexity measures the RQA provides have been useful in describing and analysing a broad range of data. It is known to be rather robust to noise and nonstationarities. Yet, one key question in empirical research concerns the confidence bounds of measured data. In the present Letter we suggest a method for estimating the confidence bounds of recurrence-based complexity measures. We study the applicability of the suggested method with model and real- life data.
Y1  - 2009
UR  - http://www.sciencedirect.com/science/journal/03759601
U6  - https://doi.org/10.1016/j.physleta.2009.04.045
SN  - 0375-9601
ER  - 
TY  - JOUR
A1  - Schinkel, Stefan
A1  - Marwan, Norbert
A1  - Kurths, Jürgen
T1  - Brain signal analysis based on recurrences
N2  - The EEG is one of the most commonly used tools in brain research. Though of high relevance in research, the data obtained is very noisy and nonstationary. In the present article we investigate the applicability of a nonlinear data analysis method, the recurrence quantification analysis (RQA), to Such data. The method solely rests on the natural property of recurrence which is a phenomenon inherent to complex systems, such as the brain. We show that this method is indeed suitable for the analysis of EEG data and that it might improve contemporary EEG analysis.
Y1  - 2009
UR  - http://www.sciencedirect.com/science/journal/09284257
U6  - https://doi.org/10.1016/j.jphysparis.2009.05.007
SN  - 0928-4257
ER  -