Results 21 to 30 of about 52,209 (206)
Teaching Ordinal Patterns to a Computer: Efficient Encoding Algorithms Based on the Lehmer Code
Entropy, 2019 Ordinal patterns are the common basis of various techniques used in the study of dynamical systems and nonlinear time series analysis. The present article focusses on the computational problem of turning time series into sequences of ordinal patterns. In
Sebastian Berger +3 more
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Ordinal Classification: Working Definition and Detection of Ordinal Structures
IEEE Access, 2020 Ordinal classification (OC) is an important niche of supervised pattern recognition, in which the classes constitute an ordinal structure. In general, the ordinal structure can be identified, either according to the natural occurrence of the current task
Peter Bellmann, Friedhelm Schwenker
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Entropy, 2023 Individual subjects’ ratings neither are metric nor have homogeneous meanings, consequently digital- labeled collections of subjects’ ratings are intrinsically ordinal and categorical.
Emanuela Furfaro, Fushing Hsieh
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Ordinal Patterns, Entropy, and EEG
Entropy, 2014 In this paper we illustrate the potential of ordinal-patterns-based methods for analysis of real-world data and, especially, of electroencephalogram (EEG) data. We apply already known (empirical permutation entropy, ordinal pattern distributions) and new
Karsten Keller +2 more
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Rhesus Monkeys Have a Counting Ability and Can Count from One to Six
Brain Sciences, 2021 Counting ability is one of the many aspects of animal cognition and has enjoyed great interest over the last couple of decades. The impetus for studying counting ability in nonhuman animals has likely come from more than a general interest in animal ...
Weiming Sun, Baoming Li, Chaolin Ma
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Permutation Entropy: Too Complex a Measure for EEG Time Series?
Entropy, 2017 Permutation entropy (PeEn) is a complexity measure that originated from dynamical systems theory. Specifically engineered to be robustly applicable to real-world data, the quantity has since been utilised for a multitude of time series analysis tasks. In
Sebastian Berger +3 more
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Applying Spatial Statistical Analysis to Ordinal Data for Soybean Iron Deficiency Chlorosis
Agronomy, 2022 Accounting for field variation patterns plays a crucial role in interpreting phenotype data and, thus, in plant breeding. Several spatial models have been developed to account for field variation.
Zhanyou Xu +2 more
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Revealed Comparative Advantage; Consistency and Stability Tests (Evidences of the Competitiveness of Agriculture, Industry and Services Sectors in the Iranian Economy) [PDF]
فصلنامه پژوهشهای اقتصادی ایران, 2021 In the present study, the competitiveness of Iran's agricultural, industrial and in global markets services sectors has been investigated and analyzed. This measurement was taken by calculating four indicators of relative comparative advantage (RCA) at ...
Mahdi Yazdani, Fahimeh Mohebinia
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Random Walk Null Models for Time Series Data
Entropy, 2017 Permutation entropy has become a standard tool for time series analysis that exploits the temporal and ordinal relationships within data. Motivated by a Kullback–Leibler divergence interpretation of permutation entropy as divergence from white noise, we ...
Daryl DeFord, Katherine Moore
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Symbolic Analysis of the Quality of Texts Translated into a Language Preserving Vowel Harmony
EntropyTo date, the ordinal pattern-based method has been applied to problems in natural and social sciences. We report, for the first time to our knowledge, an attempt to apply this methodology to a topic in the humanities.
Kazuya Hayata
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