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.
|Title of host publication||Chaos and Complexity : New Research|
|Number of pages||11|
|Publisher||Nova Science Publishers, Inc.|
|Publication status||Published - 01.12.2009|