Results 1 to 10 of about 17,530 (143)
Adaptive Multiscale Symbolic-Dynamics Entropy for Condition Monitoring of Rotating Machinery [PDF]
Entropy, 2019 Vibration data from rotating machinery working in different conditions display different properties in spatial and temporal scales. As a result, insights into spatial- and temporal-scale structures of vibration data of rotating machinery are fundamental ...
Chunhong Dou, Jinshan Lin
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Ordinal Spectrum: Mapping Ordinal Patterns into Frequency Domain [PDF]
EntropyClassical spectral analysis characterizes linear systems effectively but often fails to reveal the nonlinear temporal structure of chaotic dynamics. We introduce the ordinal spectrum, a frequency-domain characterization derived from the ordinal-pattern ...
Mario Chavez, Johann H. Martínez
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Brain Sciences, 2021 Despite mirror self-recognition being regarded as a classical indication of self-awareness, little is known about its neural underpinnings. An increasing body of evidence pointing to a role of multimodal somatosensory neurons in self-recognition guided ...
Rafael Bretas +4 more
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“Natural Laboratory Complex” for novel primate neuroscience
Frontiers in Integrative Neuroscience, 2022 We propose novel strategies for primate experimentation that are ethically valuable and pragmatically useful for cognitive neuroscience and neuropsychiatric research.
Atsushi Iriki +2 more
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Attractors in Pattern Iterations of Flat Top Tent Maps
Mathematics, 2023 Flat-topped one-dimensional maps have been used in the control of chaos in one-dimensional dynamical systems. In these applications, this mechanism is known as simple limiter control.
Luis Silva
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Statistical Tests of Symbolic Dynamics
Mathematics, 2021 A novel general method for constructing nonparametric hypotheses tests based on the field of symbolic analysis is introduced in this paper. Several existing tests based on symbolic entropy that have been used for testing central hypotheses in several ...
Fernando López +3 more
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Predictive Quantization and Symbolic Dynamics
Algorithms, 2022 Capturing long-term statistics of signals and time series is important for modeling recurrent phenomena, especially when such recurrences are a-periodic and can be characterized by the approximate repetition of variable length motifs, such as patterns in
Shlomo Dubnov
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Frontiers in Physiology, 2022 Background and PurposeMost studies on heart rate variability (HRV) in professional athletes concerned linear, time-, and frequency-domain indices, and there is lack of studies on non-linear parameters in this group. The study aimed to determine the inter-
Jakub S. Gąsior +6 more
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Measuring Dynamical Uncertainty With Revealed Dynamics Markov Models
Frontiers in Applied Mathematics and Statistics, 2019 Concepts and measures of time series uncertainty and complexity have been applied across domains for behavior classification, risk assessments, and event detection/prediction.
Aaron Bramson +5 more
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On Structured Random Matrices Defined by Matrix Substitutions
Mathematics, 2023 The structure of the random matrices introduced in this work is given by deterministic matrices—the skeletons of the random matrices—built with an algorithm of matrix substitutions with entries in a finite field of integers modulo some prime number, akin
Manuel L. Esquível, Nadezhda P. Krasii
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