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The coherence times achieved with continuous dynamical decoupling techniques are often limited by fluctuations in the driving amplitude. In this work, we use time-dependent phase-modulated continuous driving to increase the robustness…

Quantum Physics · Physics 2017-08-22 D. Farfurnik , N. Aharon , I. Cohen , Y. Hovav , A. Retzker , N. Bar-Gill

Autonomous driving highly depends on capable sensors to perceive the environment and to deliver reliable information to the vehicles' control systems. To increase its robustness, a diversified set of sensors is used, including radar…

Signal Processing · Electrical Eng. & Systems 2021-05-04 Alexander Fuchs , Johanna Rock , Mate Toth , Paul Meissner , Franz Pernkopf

The coupling signal refers to a latent physiological signal that characterizes the transformation from cardiac electrical excitation, captured by the electrocardiogram (ECG), to mechanical contraction, recorded by the phonocardiogram (PCG).…

Signal Processing · Electrical Eng. & Systems 2025-11-05 Peihong Zhang , Zhixin Li , Rui Sang , Yuxuan Liu , Yiqiang Cai , Yizhou Tan , Shengchen Li

We propose and demonstrate experimentally continuous phased dynamical decoupling (CPDD), where we apply a continuous field with discrete phase changes for quantum sensing and robust compensation of environmental and amplitude noise. CPDD…

This work presents a purely data-driven, wavelet-based framework for modal identification and reduced-order modeling of mechanical systems with assumed linear dynamics characterized by closely spaced modes with classical or non-classical…

Signal Processing · Electrical Eng. & Systems 2025-10-28 Anargyros Michaloliakos , Benjamin J. Chang , Lawrence A. Bergman , Alexander F. Vakakis

Posterior predictive p-values (ppps) have become popular tools for Bayesian model assessment, being general-purpose and easy to use. However, interpretation can be difficult because their distribution is not uniform under the hypothesis…

Methodology · Statistics 2024-02-01 Sally Paganin , Perry de Valpine

This paper revisits the fractional cointegrating relationship between ex-ante implied volatility and ex-post realized volatility. We argue that the concept of corridor implied volatility (CIV) should be used instead of the popular…

Statistical Finance · Quantitative Finance 2013-02-15 Jozef Barunik , Michaela Barunikova

Cyber-Physical Systems (CPS) in domains such as manufacturing and energy distribution generate complex time series data crucial for Prognostics and Health Management (PHM). While Deep Learning (DL) methods have demonstrated strong…

Machine Learning · Computer Science 2025-12-16 Alexander Windmann , Henrik Steude , Daniel Boschmann , Oliver Niggemann

I study how pulse to pulse phase coherence in a pulse train can survive super-broadening by extreme self phase modulation (SPM). Such pulse trains have been used in phase self-stabilizing schemes as an alternative to using a feedback…

Optics · Physics 2011-10-27 P. Kinsler

We study the onset of synchronous states in realistic chaotic neurons coupled by mutually inhibitory chemical synapses. For the realistic parameters, namely the synaptic strength and the intrinsic current, this synapse introduces…

Statistical Mechanics · Physics 2015-05-13 T. Pereira , M. S. Baptista , J. Kurths , M. B. Reyes

The human brain is ultimately responsible for all thoughts and movements that the body produces. This allows humans to successfully interact with their environment. If the brain is not functioning properly many abilities of human can be…

Neurons and Cognition · Quantitative Biology 2018-07-09 Esmaeil Seraj

Conformal Predictive Systems (CPS) offer a versatile framework for constructing predictive distributions, allowing for calibrated inference and informative decision-making. However, their applicability has been limited to scenarios adhering…

Machine Learning · Computer Science 2024-10-17 Jef Jonkers , Glenn Van Wallendael , Luc Duchateau , Sofie Van Hoecke

Video Large Language Models (VideoLLMs) face a critical bottleneck: increasing the number of input frames to capture fine-grained temporal detail leads to prohibitive computational costs and performance degradation from long context…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Hyungjin Chung , Hyelin Nam , Jiyeon Kim , Hyojun Go , Byeongjun Park , Junho Kim , Joonseok Lee , Seongsu Ha , Byung-Hoon Kim

Synchronization is a widespread phenomenon in the brain. Despite numerous studies, the specific parameter configurations of the synaptic network structure and learning rules needed to achieve robust and enduring synchronization in neurons…

Neurons and Cognition · Quantitative Biology 2023-08-15 Marius E. Yamakou , Mathieu Desroches , Serafim Rodrigues

Identifying dynamic transactions between brain regions has become increasingly important. Measurements within and across brain structures, demonstrating the occurrence of bursts of beta/gamma oscillations only during one specific phase of…

Neurons and Cognition · Quantitative Biology 2016-03-21 RD Pascual-Marqui , P Faber , T Kinoshita , Y Kitaura , K Kochi , P Milz , K Nishida , M Yoshimura

It is shown theoretically that the use of accelerating spatiotemporal quasi-phase-matching (QPM) modulation patterns in media with parametric optical interactions makes it possible to generate a time-reversed replica of the pump pulse…

Optics · Physics 2016-10-17 Michal Yachini , Boris Malomed , Alon Bahabad

Solid-state qubits hold the promise to achieve unmatched combination of sensitivity and spatial resolution. To achieve their potential, the qubits need however to be shielded from the deleterious effects of the environment. While dynamical…

Quantum Physics · Physics 2016-11-26 Masashi Hirose , Clarice D. Aiello , Paola Cappellaro

Lossy image coding standards such as JPEG and MPEG have successfully achieved high compression rates for human consumption of multimedia data. However, with the increasing prevalence of IoT devices, drones, and self-driving cars, machines…

Computer Vision and Pattern Recognition · Computer Science 2023-10-03 Chen-Hsiu Huang , Ja-Ling Wu

A computationally quick and conceptually simple method to recover time delay of the chaotic system from scalar time series is developed in this paper. We show that the orbits in the incomplete two-dimensional reconstructed phase-space will…

Chaotic Dynamics · Physics 2016-11-15 Shengli Zhu , Lu Gan

Medical vision-language segmentation models suffer from catastrophic forgetting when adapting to new anatomical structures, requiring complete retraining that limits their clinical deployment. Although continual learning approaches have…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Ziyuan Gao
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