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We present an approach which enables to identify phase synchronization in coupled chaotic oscillators without having to explicitly measure the phase. We show that if one defines a typical event in one oscillator and then observes another…

Statistical Mechanics · Physics 2009-11-13 T. Pereira , M. S. Baptista , J. Kurths

Multivariate time series (MTS) analysis prevails in real-world applications such as finance, climate science and healthcare. The various self-attention mechanisms, the backbone of the state-of-the-art Transformer-based models, efficiently…

Machine Learning · Computer Science 2023-11-21 Quang Minh Nguyen , Lam M. Nguyen , Subhro Das

Many rare event transitions involve multiple collective variables (CVs) and the most appropriate combination of CVs is generally unknown a priori. We thus introduce a new method, contour forward flux sampling (cFFS), to study rare events…

Statistical Mechanics · Physics 2019-01-14 Ryan S. DeFever , Sapna Sarupria

This paper develops a novel statistical approach to characterize temporally localised cross-oscillatory interactions between channels in a functional brain network. Brain signals are generally nonstationary and the proposed framework uses…

Methodology · Statistics 2026-02-10 Haibo Wu , Marina I. Knight , Hernando Ombao

An approach is presented for coupled chaotic systems, estimating an inferior bound value for the absolute phase difference, in order to say that phase synchronization is present. This approach shows that synchronicity in phase implies…

Classical Physics · Physics 2007-06-22 M. S. Baptista , T. Pereira , J. Kurths

This paper proposes a capacitor voltage synchronizing control (CVSC) system for the regulation of full-scale wind power generator-supplied power systems (FWPS). The capacitor combined with the inverter of a full-scale wind power generator…

Systems and Control · Electrical Eng. & Systems 2023-05-17 Yang Liu

Connected vehicles (CVs) can capture and transmit detailed data like vehicle position, speed and so on through vehicle-to-vehicle and vehicle-to-infrastructure communications. The wealth of CV data provides new opportunities to improve the…

Applications · Statistics 2018-06-08 Lei Lin

In a quasi-1D thermal convective system consisting of a large array of nonlinearly coupled oscillators, clustering is the way to achieve a regime of mostly antiphase synchronized oscillators. This regime is characterized by a spatiotemporal…

Chaotic Dynamics · Physics 2011-03-10 M. A. Miranda , J. Burguete

Though the notion of phase synchronization has been well studied in chaotic dynamical systems without delay, it has not been realized yet in chaotic time-delay systems exhibiting non-phase coherent hyperchaotic attractors. In this article…

Chaotic Dynamics · Physics 2009-11-11 D. V. Senthilkumar , M. Lakshmanan , J. Kurths

Accurate phase demodulation is critical for vital sign detection using millimeter-wave radar. However, in complex environments, time-varying DC offsets and phase imbalances can severely degrade demodulation performance. To address this, we…

Signal Processing · Electrical Eng. & Systems 2025-05-14 Shuai Sun , Chong-Xi Liang , Chengwei Ye , Huanzhen Zhang , Kangsheng Wang

A new method is introduced for analysis of interactions between time-dependent coupled oscillators, based on the signals they generate. It distinguishes unsynchronized dynamics from noise-induced phase slips, and enables the evolution of…

Data Analysis, Statistics and Probability · Physics 2012-08-09 Tomislav Stankovski , Andrea Duggento , Peter V. E. McClintock , Aneta Stefanovska

Quantum phase transitions in many-body systems are fundamentally characterized by complex correlation structures, which pose computational challenges for conventional methods in large systems. To address this, we propose a hybrid…

Quantum Physics · Physics 2026-02-03 Jin-Long Chen , Xin Li , Zhang-Qi Yin

In systems of coupled oscillators, the effects of complex signaling can be captured by time delays and phase shifts. Here, we show how time delays and phase shifts lead to different oscillator dynamics and how synchronization rates can be…

Adaptation and Self-Organizing Systems · Physics 2018-03-30 David J. Jörg , Luis G. Morelli , Saúl Ares , Frank Jülicher

Circular variables such as phase or orientation have received considerable attention throughout the scientific and engineering communities and have recently been quite prominent in the field of neuroscience. While many analytic techniques…

Neurons and Cognition · Quantitative Biology 2009-06-21 Charles F. Cadieu , Kilian Koepsell

Hypercomplex signal processing (HSP) offers powerful tools for analyzing and processing multidimensional signals by explicitly exploiting inter-dimensional correlations through Clifford algebra. In recent years, hypercomplex formulations of…

Signal Processing · Electrical Eng. & Systems 2026-03-02 Kumar Vijay Mishra , Henry Arguello , Brian M. Sadler

Phase synchrony information plays a crucial role in analyzing functional brain connectivity and identifying brain activities. A widely adopted feature extraction pipeline, composed of preprocessing, selection of EEG acquisition channels,…

Signal Processing · Electrical Eng. & Systems 2023-10-12 Xu Niu , Na Lu , Huan Luo , Ruofan Yan

Machine learning components such as deep neural networks are used extensively in Cyber-Physical Systems (CPS). However, they may introduce new types of hazards that can have disastrous consequences and need to be addressed for engineering…

Machine Learning · Computer Science 2020-04-21 Dimitrios Boursinos , Xenofon Koutsoukos

We present an approach which enables to state about the existence of phase synchronization in coupled chaotic oscillators without having to measure the phase. This is done by observing the oscillators at special times, and analyzing whether…

Statistical Mechanics · Physics 2009-11-13 T. Pereira , M. S. Baptista , J. Kurths

We examine the use of synchronization as a mechanism for extracting parameter and state information from experimental systems. We focus on important aspects of this problem that have received little attention previously, and we explore them…

The conditional particle filter (CPF) is a promising algorithm for general hidden Markov model smoothing. Empirical evidence suggests that the variant of CPF with backward sampling (CBPF) performs well even with long time series. Previous…

Computation · Statistics 2019-08-29 Anthony Lee , Sumeetpal S. Singh , Matti Vihola