scholarly journals Characterizing signal encoding and transmission in class I and class II neurons via ordinal time-series analysis

2020 ◽  
Vol 30 (1) ◽  
pp. 013123 ◽  
Author(s):  
C. Estarellas ◽  
M. Masoliver ◽  
C. Masoller ◽  
Claudio R. Mirasso
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Class Ii ◽  
Class I ◽  
Series Analysis ◽  
Signal Encoding ◽  
Ordinal Time Series

The Use of Ordinal Time-Series Analysis In Assessing Policy Inputs and Impacts

1986 ◽  
Vol 22 (1) ◽  
pp. 77-93 ◽  
Author(s):  
Diana M. Dinitto ◽  
Reuben R. Mcdaniel ◽  
Timothy W. Ruefli ◽  
James B. Thomas
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Series Analysis ◽  
Ordinal Time Series

Ordinal time series analysis

2005 ◽  
Vol 182 (3-4) ◽  
pp. 229-238 ◽  
Author(s):  
Christoph Bandt
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Series Analysis ◽  
Ordinal Time Series

TIME SERIES FROM THE ORDINAL VIEWPOINT

2007 ◽  
Vol 07 (02) ◽  
pp. 247-272 ◽  
Author(s):  
KARSTEN KELLER ◽  
MATHIEU SINN ◽  
JAN EMONDS
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
New Approach ◽  
Ordinal Information ◽  
Invariance Properties ◽  
Series Analysis ◽  
Order Relations ◽  
Ordinal Patterns ◽  
Ordinal Time Series ◽  
Ordinal Pattern

Ordinal time series analysis is a new approach to the investigation of long and complex time series, which bases on ordinal patterns describing the order relations between the values of a time series. In this paper we consider ordinal time series analysis from the conceptional viewpoint. In particular, we introduce ordinal processes as models for ordinal time series analysis and discuss the structure of ordinal pattern distributions obtained from them. Special emphasis is on the relation of ordinal time series analysis to symbolic dynamics and to a transformation extracting the whole ordinal information contained in a time series. Finally, we consider invariance properties of ordinal time series analysis.

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