Results 11 to 20 of about 13,329 (248)
Permutation Entropy for Signal Analysis [PDF]
Discrete Mathematics & Theoretical Computer ScienceShannon Entropy is the preeminent tool for measuring the level of uncertainty (and conversely, information content) in a random variable. In the field of communications, entropy can be used to express the information content of given signals (represented
Bill Kay +6 more
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Calculating Permutation Entropy without Permutations [PDF]
Complexity, 2020 A method for analyzing sequential data sets, similar to the permutation entropy one, is discussed. The characteristic features of this method are as follows: it preserves information about equal values, if any, in the embedding vectors; it is exempt from
Alexander K. Vidybida
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Permutation Entropy Based on Non-Uniform Embedding [PDF]
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
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Permutation Entropy for Graph Signals [PDF]
IEEE Transactions on Signal and Information Processing over Networks, 2022 Entropy metrics (for example, permutation entropy) are nonlinear measures of irregularity in time series (one-dimensional data). Some of these entropy metrics can be generalised to data on periodic structures such as a grid or lattice pattern (two-dimensional data) using its symmetry, thus enabling their application to images.
John Stewart Fabila-Carrasco +2 more
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Generalized weighted permutation entropy
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2022 A novel heuristic approach is proposed here for time series data analysis, dubbed Generalized weighted permutation entropy, which amalgamates and generalizes beyond their original scope two well established data analysis methods: Permutation entropy and Weighted permutation entropy.
Darko Stosic +3 more
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On the automatic parameter selection for permutation entropy [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2020 Permutation Entropy (PE) is a cost effective tool for summarizing the complexity of a time series. It has been used in many applications including damage detection, disease forecasting, detection of dynamical changes, and financial volatility analysis.
Audun Myers, Firas A. Khasawneh
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The asymptotic distribution of the permutation entropy
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2023 Ordinal patterns serve as a robust symbolic transformation technique, enabling the unveiling of latent dynamics within time series data. This methodology involves constructing histograms of patterns, followed by the calculation of both entropy and statistical complexity—an avenue yet to be fully understood in terms of its statistical properties.
A. A. Rey +3 more
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Permutation Entropy and Its Niche in Hydrology: A Review. [PDF]
Entropy (Basel)One effective method for analyzing complexity involves applying information measures to time series derived from observational data. Permutation entropy (PE) is one such measure designed to quantify the degree of disorder or complexity within a time series by examining the order relations among its values.
Mihailović DT.
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Frontiers in Physics, 2023 Most of the existing studies on the improvement of entropy are based on the theory of single entropy, ignoring the relationship between one entropy and another. Inspired by the synergistic relationship between bubble entropy (BE) and permutation entropy (
Xinru Jiang +3 more
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Modeling of investment attractiveness of countries using entropy analysis of regional stock markets [PDF]
Global Journal of Environmental Science and Management, 2019 The current study focuses on the problem of determining investment attrаctiveness of countries by means of monitoring regional stock markets. The method of using the permutation entropy as a model of investment attractiveness estimation is suggested.
H. Danylchuk +3 more
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