Journal Article10.1016/J.PHYSLETA.2007.01.085
Testing for phase synchronization
TL;DR: In this article, an analytic significance level for a frequently used phase synchronization measure is derived for a system of coupled oscillators, and its performance is demonstrated for a single-input single-output (SISO) system.
read more
About: This article is published in Physics Letters A. The article was published on 02 Jul 2007. The article focuses on the topics: Phase synchronization & Synchronization (computer science).
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Phase Synchronization Analysis of EEG Signals: An Evaluation Based on Surrogate Tests
TL;DR: An intensive computation study on PS analysis based on surrogate tests with artificial surrogate data generated by shuffling the rank order, the phase spectra, or the instantaneous frequency of original EEG signals shows that the phase-shuffled surrogate method is workable for significance test of estimated PS index.
121
Measuring group synchrony: a cluster-phase method for analyzing multivariate movement time-series.
TL;DR: The cluster-phase method of Frank and Richardson (2010) was used to analyze movement data from the rocking chair movements of six-member groups who rocked their chairs while seated in a circle facing the center, and the group level synchrony measure was able to distinguish between situations where synchrony would have been possible and situations where it would be impossible.
On a test statistic for the Kuramoto order parameter of synchronization: An illustration for group synchronization during rocking chairs
TL;DR: In this article, a quantitative approach to detect phase synchronization in noisy experimental multivariate data is discussed, and a test statistic based on the Kuramoto order parameter is derived for rejecting the null hypothesis of zero phase synchronization at given significance levels.
77
Can spurious indications for phase synchronization due to superimposed signals be avoided
TL;DR: The findings indicate that the unweighted and weighted phase lag index are less prone to the influence of common sources but that this advantage may lead to constrictions limiting the applicability of these methods.
44
Inferring functional neural connectivity with phase synchronization analysis: a review of methodology.
TL;DR: The definitions of instantaneous phase, the indexes of phase synchronization and their significance test, the issues that may affect the detection of phase synchronized signals, and the extensions ofphase synchronization analysis are discussed.
References
Numerical recipes
TL;DR: This section discusses a particular type of low-pass filter, well-adapted for data smoothing, and termed variously Savitzky-Golay, least-squares, or DISPO (Digital Smoothing Polynomial) filters.
19K
•Book
Convergence of Probability Measures
Patrick Billingsley
- 01 Jan 1968
TL;DR: Weak Convergence in Metric Spaces as discussed by the authors is one of the most common modes of convergence in metric spaces, and it can be seen as a form of weak convergence in metric space.
15K
Synchronization in chaotic systems
TL;DR: This chapter describes the linking of two chaotic systems with a common signal or signals and highlights that when the signs of the Lyapunov exponents for the subsystems are all negative the systems are synchronized.
10.5K
•Book
Synchronization: A Universal Concept in Nonlinear Sciences
Arkady Pikovsky,Michael Rosenblum,Jürgen Kurths +2 more
- 01 Jan 2001
TL;DR: This work discusseschronization of complex dynamics by external forces, which involves synchronization of self-sustained oscillators and their phase, and its applications in oscillatory media and complex systems.
7.5K
•Book
Probability and Measure
Patrick Billingsley
- 01 Jan 1979
TL;DR: In this paper, the convergence of distributions is considered in the context of conditional probability, i.e., random variables and expected values, and the probability of a given distribution converging to a certain value.