Results 21 to 30 of about 189,338 (155)
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2021 The estimation of the qualitative behaviour of fractional Brownian motion is an important topic for modelling real-world applications. Permutation entropy is a well-known approach to quantify the complexity of univariate time series in a scalar-valued ...
Marisa Mohr +2 more
doaj +1 more source
Statistically Significant Pattern Mining with Ordinal Utility [PDF]
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020 Statistically significant patterns mining (SSPM) is an essential and challenging data mining task in the field of knowledge discovery in databases (KDD), in which each pattern is evaluated via a hypothesis test. Our study aims to introduce a preference relation into patterns and to discover the most preferred patterns under the constraint of ...
Thien Q. Tran +3 more
openaire +2 more sources
Ordinal patterns in long‐range dependent time series [PDF]
Scandinavian Journal of Statistics, 2020 AbstractWe analyze the ordinal structure of long‐range dependent time series. To this end, we use so called ordinal patterns which describe the relative position of consecutive data points. We provide two estimators for the probabilities of ordinal patterns and prove limit theorems in different settings, namely stationarity and (less restrictive ...
Annika Betken +5 more
openaire +2 more sources
Ordinal synchronization: Using ordinal patterns to capture interdependencies between time series [PDF]
Chaos, Solitons & Fractals, 2019 We introduce Ordinal Synchronization ($OS$) as a new measure to quantify synchronization between dynamical systems. $OS$ is calculated from the extraction of the ordinal patterns related to two time series, their transformation into $D$-dimensional ordinal vectors and the adequate quantification of their alignment.
I. Echegoyen +4 more
openaire +4 more sources
The frequency of pattern occurrence in random walks [PDF]
Discrete Mathematics & Theoretical Computer Science, 2015 In the past decade, the use of ordinal patterns in the analysis of time series and dynamical systems has become an important tool. Ordinal patterns (otherwise known as a permutation patterns) are found in time series by taking $n$ data points at evenly ...
Sergi Elizalde, Megan Martinez
doaj +1 more source
Statistical properties of the entropy from ordinal patterns
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2022 The ultimate purpose of the statistical analysis of ordinal patterns is to characterize the distribution of the features they induce. In particular, knowing the joint distribution of the pair entropy-statistical complexity for a large class of time series models would allow statistical tests that are unavailable to date.
E. T. C. Chagas +5 more
openaire +4 more sources
Continuous ordinal patterns: Creating a bridge between ordinal analysis and deep learning
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2023 We introduce a generalization of the celebrated ordinal pattern approach for the analysis of time series, in which these are evaluated in terms of their distance to ordinal patterns defined in a continuous way. This allows us to naturally incorporate information about the local amplitude of the data and to optimize the ordinal pattern(s) to the problem
openaire +5 more sources
CHARACTERIZATION OF SAR IMAGES WITH WEIGHTED AMPLITUDE TRANSITION GRAPHS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 We propose a new technique for SAR image texture characterization based on ordinal pattern transition graphs. The proposal consists in (i) transforming a 2-D patch of data into a time series using a Hilbert Space Filling Curve, (ii) building an Ordinal ...
E. T. C. Chagas +3 more
doaj +1 more source
Permutation Entropy Based on Non-Uniform Embedding
Entropy, 2018 A novel visualization scheme for permutation entropy is presented in this paper. The proposed scheme is based on non-uniform attractor embedding of the investigated time series.
Mei Tao +4 more
doaj +1 more source
Fuzzy Windows with Gaussian Processed Labels for Ordinal Image Scoring Tasks
Applied Sciences, 2023 In this paper, we propose a Fuzzy Window with the Gaussian Processed Label (FW-GPL) method to mitigate the overlap problem in the neighboring ordinal category when scoring images.
Cheng Kang, Xujing Yao, Daniel Novak
doaj +1 more source