We deal here with the issue of determinism versus randomness in time series (TS), with the goal of identifying their relative importance in a given TS. To this end we extend (i) the use of ordinal patterns based probability distribution functions associated to a TS [C. Bandt and B. Pompe, Phys. Rev. Lett. 88, 174102 (2002)] and (ii) the so-called Amigó paradigm of forbidden/missing patterns [J.M. Amigó et al., Europhys. Lett. 79, 50001 (2007)], to analyze deterministic finite TS contaminated with strong additive noises of different correlation-degree. Useful information on the deterministic component of the original time series is obtained with the help of the ...
In this paper we illustrate the potential of ordinal-patterns-based methods for analysis of real-wor...
In 2002, in a seminal article, Bandt and Pompe proposed a new methodology for the analysis of comple...
Permutation entropy has become a standard tool for time series analysis that exploits the temporal a...
We deal here with the issue of determinism versus randomness in time series (TS), with the goal of i...
We deal here with the issue of determinism versus randomness in time series. One wishes to identify ...
Recent research aiming at the distinction between deterministic or stochastic behavior in observatio...
This paper deals with the distinction between white noise and deterministic chaos in multivariate no...
It has been established that the count of ordinal patterns, which do not occur in a time series, cal...
When calculating the Bandt and Pompe ordinal pattern distribution from given time series at depth D,...
By appealing to a long list of different nonlinear maps we review the characterization of time serie...
By appealing to a long list of different nonlinear maps we review the characterization of ...
This is a paper in the intersection of time series analysis and complexity theory that presents new ...
The ultimate purpose of the statistical analysis of ordinal patterns is to characterize the distribu...
One of the most important aspects of time series is their degree of stochasticity vs. chaoticity. Si...
Strategies based on the extraction of measures from ordinal patterns transformation, such as probabi...
In this paper we illustrate the potential of ordinal-patterns-based methods for analysis of real-wor...
In 2002, in a seminal article, Bandt and Pompe proposed a new methodology for the analysis of comple...
Permutation entropy has become a standard tool for time series analysis that exploits the temporal a...
We deal here with the issue of determinism versus randomness in time series (TS), with the goal of i...
We deal here with the issue of determinism versus randomness in time series. One wishes to identify ...
Recent research aiming at the distinction between deterministic or stochastic behavior in observatio...
This paper deals with the distinction between white noise and deterministic chaos in multivariate no...
It has been established that the count of ordinal patterns, which do not occur in a time series, cal...
When calculating the Bandt and Pompe ordinal pattern distribution from given time series at depth D,...
By appealing to a long list of different nonlinear maps we review the characterization of time serie...
By appealing to a long list of different nonlinear maps we review the characterization of ...
This is a paper in the intersection of time series analysis and complexity theory that presents new ...
The ultimate purpose of the statistical analysis of ordinal patterns is to characterize the distribu...
One of the most important aspects of time series is their degree of stochasticity vs. chaoticity. Si...
Strategies based on the extraction of measures from ordinal patterns transformation, such as probabi...
In this paper we illustrate the potential of ordinal-patterns-based methods for analysis of real-wor...
In 2002, in a seminal article, Bandt and Pompe proposed a new methodology for the analysis of comple...
Permutation entropy has become a standard tool for time series analysis that exploits the temporal a...