Abstract
Ordinal time series analysis is a new approach to the qualitative investigation of long and complex time series. The idea behind it is to transform a given time series into a series of ordinal patterns each describing the order relations between the present and a fixed number of equidistant past values at a given time. Here we consider ordinal pattern distributions and some measures derived from them in order to detect differences between EEG data.
Original language | English |
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Title of host publication | Chaos and Complexity : New Research |
Number of pages | 11 |
Publisher | Nova Science Publishers, Inc. |
Publication date | 01.12.2009 |
Pages | 239-249 |
ISBN (Print) | 9781604568417 |
Publication status | Published - 01.12.2009 |