Comparative analysis of the original and amplitude permutations

Yao, Wenpo; Yao, Wenli; Wang, Jun

doi:10.1016/j.physleta.2022.127977

Cited by 5 publications

(14 citation statements)

References 16 publications

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“…If several components have equal values, they should be arranged in ascending order according to their k values. The indexes of equal values are modified to be the same as those in their corresponding groups, e.g., by the smallest or largest index [57]. In permutation entropy, ordinal patterns are labels of different vectors; therefore, the original permutation and amplitude permutation make no difference [57].…”

Section: Weighted Permutation Entropymentioning

confidence: 99%

“…The indexes of equal values are modified to be the same as those in their corresponding groups, e.g., by the smallest or largest index [57]. In permutation entropy, ordinal patterns are labels of different vectors; therefore, the original permutation and amplitude permutation make no difference [57]. In this manner, every vector Y s (n) in the phase space can be hit to obtain a set of permutations π n = {k 1 , k 2 , • • • , k m }.…”

Section: Weighted Permutation Entropymentioning

confidence: 99%

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Multiscale Weighted Permutation Entropy Analysis of Schizophrenia Magnetoencephalograms

Bai

Yao

Wang

et al. 2022

Entropy

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Schizophrenia is a neuropsychiatric disease that affects the nonlinear dynamics of brain activity. The primary objective of this study was to explore the complexity of magnetoencephalograms (MEG) in patients with schizophrenia. We combined a multiscale method and weighted permutation entropy to characterize MEG signals from 19 schizophrenia patients and 16 healthy controls. When the scale was larger than 42, the MEG signals of schizophrenia patients were significantly more complex than those of healthy controls (p<0.004). The difference in complexity between patients with schizophrenia and the controls was strongest in the frontal and occipital areas (p<0.001), and there was almost no difference in the central area. In addition, the results showed that the dynamic range of MEG complexity is wider in healthy individuals than in people with schizophrenia. Overall, the multiscale weighted permutation entropy method reliably quantified the complexity of MEG from schizophrenia patients, contributing to the development of potential magnetoencephalographic biomarkers for schizophrenia.

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Section: Weighted Permutation Entropymentioning

confidence: 99%

Section: Weighted Permutation Entropymentioning

confidence: 99%

Multiscale Weighted Permutation Entropy Analysis of Schizophrenia Magnetoencephalograms

Bai

Yao

Wang

et al. 2022

Entropy

Self Cite

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“…The existence of forbidden permutations means that division-based parameters (e.g., the Kullback-Leibler distance) should not be directly applied in quantitative TIR and AIR [9,37]. Moreover, the two basic ordinal patterns, i.e., original and amplitude permutations [38], are different. Original permutation consists of the indexes of reorganized values in the original vector, and is not a direct reflection of the amplitude structure of the vectors.…”

Section: Introductionmentioning

confidence: 99%

“…Through comparative analysis of the vector structure and its permutation, the present authors have previously corrected the conceptual error underlying the original symmetric permutations used to quantify TIR [9,37,38], and derived the concept of amplitude-reversibility based on the symmetric permutations [1]. The nonequilibrium descriptors provided by TIR and the novel AIR are linked-they are different theoretical concepts, but experimental analysis has shown that they produce consistent findings [1,9,37].…”

Section: Introductionmentioning

confidence: 99%

“…(3) Permutation analysis plays an important role in quantifying TIR and AIR [1,8,9,10,11]. Original and amplitude permutations both convey basic vector structures [38], but could they be further improved for TIR and AIR analysis? Overall, the associations among TIR and AIR, and their quantification based on ordinal patterns and physical implications, require further study.…”

Section: Introductionmentioning

confidence: 99%

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Comparative analysis of time irreversibility and amplitude irreversibility based on joint permutation

Yao,

et al. 2022

Preprint

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Although time irreversibility (TIR) and amplitude irreversibility (AIR) are relevant concepts for nonequilibrium analysis, their association has received little attention. This paper conducts a systematic comparative analysis of the relationship between TIR and AIR based on statistical descriptions and numerical simulations. To simplify the quantification of TIR and AIR, the amplitude permutation and global information of the associated vector are combined to produce a joint probability estimation. Chaotic logistic, Henon, and Lorenz series are generated to evaluate TIR and AIR according to surrogate theory, and the distributions of joint permutations for these model series are measured to compare the degree of TIR and AIR. The joint permutation TIR and AIR are then used to investigate nonequilibrium pathological features in epileptic electroencephalography data. Test results suggest that epileptic brain electrical activities, particular those during the onset of seizure, manifest higher nonequilibrium characteristics. According to the statistical definitions and targeted pairs of joint permutations in the chaotic model data, TIR and AIR are fundamentally different nonequilibrium descriptors from time-and amplitude-reversibility, respectively, and thus require different forms of numerical analysis. At the same time, TIR and AIR both provide measures for fluctuation theorems associated with nonequilibrium processes, and have similar probabilistic differences in the pairs of joint permutations and consistent outcomes when used to analyze both the model series and real-world signals. Overall, comparative analysis of TIR and AIR contributes to our understanding of nonequilibrium features and broadens the scope of quantitative nonequilibrium measures. Additionally, the construction of joint permutations contributes to the development of symbolic time series analysis.

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Comparative analysis of time irreversibility and amplitude irreversibility based on joint permutation

Yao

Yao²,

Xu³

et al. 2023

Communications in Nonlinear Science and Numerical Simulation

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Comparative analysis of the original and amplitude permutations

Cited by 5 publications

References 16 publications

Multiscale Weighted Permutation Entropy Analysis of Schizophrenia Magnetoencephalograms

Multiscale Weighted Permutation Entropy Analysis of Schizophrenia Magnetoencephalograms

Comparative analysis of time irreversibility and amplitude irreversibility based on joint permutation

Comparative analysis of time irreversibility and amplitude irreversibility based on joint permutation

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