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This paper proposes a novel, highly effective spectrum sensing algorithm for cognitive radio and whitespace applications. The proposed spectral covariance sensing (SCS) algorithm exploits the different statistical correlations of the…

网络与互联网体系结构 · 计算机科学 2010-05-07 Jaeweon Kim , Jeffrey G. Andrews

Co-saliency detection aims to discover the common and salient foregrounds from a group of relevant images. For this task, we present a novel adaptive graph convolutional network with attention graph clustering (GCAGC). Three major…

计算机视觉与模式识别 · 计算机科学 2020-03-16 Kaihua Zhang , Tengpeng Li , Shiwen Shen , Bo Liu , Jin Chen , Qingshan Liu

Observing and timing a group of millisecond pulsars (MSPs) with high rotational stability enables the direct detection of gravitational waves (GWs). The GW signals can be identified from the spatial correlations encoded in the…

The phenomenon of Gravitational Wave (GW) analysis has grown in popularity as technology has advanced and the process of observing gravitational waves has become more precise. Although the sensitivity and the frequency of observation of GW…

机器学习 · 计算机科学 2023-11-07 Elena-Simona Apostol , Ciprian-Octavian Truică

Earthquake detection is essential for earthquake early warning (EEW) systems. Traditional methods struggle with low signal-to-noise ratios and single-station reliance, limiting their effectiveness. We propose a Spatio-Temporal Graph…

机器学习 · 计算机科学 2025-03-17 Suchanun Piriyasatit , Ercan Engin Kuruoglu , Mehmet Sinan Ozeren

Gravitational Wave (GW) events are physical processes that significantly perturbate space-time, e.g. compact binary coalescenses, causing the production of GWs. The detection of GWs by a worldwide network of advanced interferometers offer…

We report results of a public data-analysis challenge, hosted on the open data-science platform Kaggle, to detect simulated continuous gravitational-wave signals (CWs). These are weak signals from rapidly spinning neutron stars that remain…

When gravitational waves (GWs) propagate near massive objects, they undergo gravitational lensing that imprints lens model dependent modulations on the waveform. This effect provides a powerful tool for cosmological and astrophysical…

广义相对论与量子宇宙学 · 物理学 2026-05-12 Zheng Qin , Tian-Yang Sun , Bo-Yuan Li , Jing-Fei Zhang , Xiao Guo , Xin Zhang

We demonstrate how a morphological veto involving Bayesian statistics can improve the receiver-operating characteristic (ROC) curves of the current search for core-collapse supernovae (CCSNe) as implemented by the coherent Waveburst (cWB)…

高能天体物理现象 · 物理学 2018-02-22 Kiranjyot Gill , Wenhui Wang , Oscar Valdez , Marek Szczepanczyk , Michele Zanolin , Soma Mukherjee

This work investigates the detection of binary neutron stars gravitational wave based on convolutional neural network (CNN). To promote the detection performance and efficiency, we proposed a scheme based on wavelet packet (WP)…

天体物理仪器与方法 · 物理学 2023-12-27 Baijiong Lin , Xiangru Li , Woliang Yu

Gravitational-wave searches for cosmic strings are currently hindered by the presence of detector glitches, some classes of which strongly resemble cosmic string signals. This confusion greatly reduces the efficiency of searches. A…

天体物理仪器与方法 · 物理学 2024-01-23 Quirijn Meijer , Melissa Lopez , Daichi Tsuna , Sarah Caudill

We combine hierarchical Bayesian modeling with a flow-based deep generative network, in order to demonstrate that one can efficiently constraint numerical gravitational wave (GW) population models at a previously intractable complexity.…

天体物理仪器与方法 · 物理学 2020-07-07 Kaze W. K. Wong , Gabriella Contardo , Shirley Ho

Assessing the probability that two or more gravitational waves (GWs) are lensed images of the same source requires an understanding of the image properties, including their relative phase shifts in strong lensing (SL). For non-precessing,…

广义相对论与量子宇宙学 · 物理学 2021-03-31 Jose María Ezquiaga , Daniel E. Holz , Wayne Hu , Macarena Lagos , Robert M. Wald

In this paper, we consider the problem of joint sparsity pattern recovery in a distributed sensor network. The sparse multiple measurement vector signals (MMVs) observed by all the nodes are assumed to have a common (but unknown) sparsity…

信息论 · 计算机科学 2016-01-27 Gang Li , Thakshila Wimalajeewa , Pramod K. Varshney

As of this moment, fifty gravitational waves (GW) detections have been announced, thanks to the observational efforts of the LIGO-Virgo Collaboration, working with the Advanced LIGO and the Advanced Virgo interferometers. The detection of…

天体物理仪器与方法 · 物理学 2021-12-30 Filip Morawski , Michał Bejger , Elena Cuoco , Luigia Petre

We present a flexible model to describe the effects of generic deviations of observed gravitational wave signals from modeled waveforms in the LIGO and Virgo gravitational wave detectors. With the detection of 11 gravitational wave events…

The advent of sensitive gravitational wave (GW) detectors, coupled with wide-field, high cadence optical time-domain surveys, raises the possibility of the first joint GW-electromagnetic (EM) detections of core-collapse supernovae (CCSNe).…

高能天体物理现象 · 物理学 2022-06-15 Kiranjyot Gill , Griffin Hosseinzadeh , Edo Berger , Michele Zanolin , Marek Szczepanczyk

Steady-State Visual Evoked Potentials (SSVEPs) are neural oscillations from the parietal and occipital regions of the brain that are evoked from flickering visual stimuli. SSVEPs are robust signals measurable in the electroencephalogram…

A yet undetected class of GW signals is represented by the close encounters between compact objects in highly-eccentric e~1 orbits, that can occur in binary systems formed in dense environments such as globular clusters. The expected…

广义相对论与量子宇宙学 · 物理学 2025-09-26 Federico De Santi , Massimiliano Razzano , Francesco Fidecaro , Luca Muccillo , Lucia Papalini , Barbara Patricelli

Gravitational wave lensing, particularly microlensing by compact dark matter (DM), offers a unique avenue to probe the nature of dark matter. However, conventional detection methods are often computationally expensive, inefficient, and…

天体物理仪器与方法 · 物理学 2025-09-08 Ao Liu , Tonghua Liu , Dejiang Li , Cuihong Wen , Jieci Wang , Kai Liao , Jiaxing Cui , Huan Zhou