4,027 research outputs found
Characterizing Intermittency of 4-Hz Quasi-periodic Oscillation in XTE J1550-564 using Hilbert-Huang Transform
We present the time-frequency analysis results based on the Hilbert-Huang
transform (HHT) for the evolution of a 4-Hz low-frequency quasi-periodic
oscillation (LFQPO) around the black hole X-ray binary XTE J1550-564. The
origin of LFQPOs is still debated. To understand the cause of the peak
broadening, we utilized a recently developed time-frequency analysis, HHT, for
tracking the evolution of the 4-Hz LFQPO from XTE J1550 564. By adaptively
decomposing the ~4-Hz oscillatory component from the light curve and acquiring
its instantaneous frequency, the Hilbert spectrum illustrates that the LFQPO is
composed of a series of intermittent oscillations appearing occasionally
between 3 Hz and 5 Hz. We further characterized this intermittency by computing
the confidence limits of the instantaneous amplitudes of the intermittent
oscillations, and constructed both the distributions of the QPO's high and low
amplitude durations, which are the time intervals with and without significant
~4-Hz oscillations, respectively. The mean high amplitude duration is 1.45 s
and 90% of the oscillation segments have lifetimes below 3.1 s. The mean low
amplitude duration is 0.42 s and 90% of these segments are shorter than 0.73 s.
In addition, these intermittent oscillations exhibit a correlation between the
oscillation's rms amplitude and mean count rate. This correlation could be
analogous to the linear rms-flux relation found in the 4-Hz LFQPO through
Fourier analysis. We conclude that the LFQPO peak in the power spectrum is
broadened owing to intermittent oscillations with varying frequencies, which
could be explained by using the Lense-Thirring precession model.Comment: 27 pages, 9 figures, accepted for publication in The Astrophysical
Journa
Congestion Control for Machine-Type Communications in LTE-A Networks
Collecting data from a tremendous amount of Internet-of-Things (IoT) devices for next generation networks is a big challenge. A large number of devices may lead to severe congestion in Radio Access Network (RAN) and Core Network (CN). 3GPP has specified several mechanisms to handle the congestion caused by massive amounts of devices. However, detailed settings and strategies of them are not defined in the standards and are left for operators. In this paper, we propose two congestion control algorithms which efficiently reduce the congestion. Simulation results demonstrate that the proposed algorithms can achieve 20~40% improvement regarding accept ratio, overload degree and waiting time compared with those in LTE-A
PPFL: A Personalized Federated Learning Framework for Heterogeneous Population
Personalization aims to characterize individual preferences and is widely
applied across many fields. However, conventional personalized methods operate
in a centralized manner and potentially expose the raw data when pooling
individual information. In this paper, with privacy considerations, we develop
a flexible and interpretable personalized framework within the paradigm of
Federated Learning, called PPFL (Population Personalized Federated Learning).
By leveraging canonical models to capture fundamental characteristics among the
heterogeneous population and employing membership vectors to reveal clients'
preferences, it models the heterogeneity as clients' varying preferences for
these characteristics and provides substantial insights into client
characteristics, which is lacking in existing Personalized Federated Learning
(PFL) methods. Furthermore, we explore the relationship between our method and
three main branches of PFL methods: multi-task PFL, clustered FL, and
decoupling PFL, and demonstrate the advantages of PPFL. To solve PPFL (a
non-convex constrained optimization problem), we propose a novel random block
coordinate descent algorithm and present the convergence property. We conduct
experiments on both pathological and practical datasets, and the results
validate the effectiveness of PPFL.Comment: 38 pages, 11 figure
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