94 research outputs found
H
An H∞ consensus problem of multiagent systems is studied by introducing disturbances into the systems. Based on H∞ control theory and consensus theory, a condition is derived to guarantee the systems both reach consensus and have a certain H∞ property. Finally, an example is worked out to demonstrate the effectiveness of the theoretical results
Modeling and Detecting Network Communities with the Fusion of Node Attributes
As a fundamental structure in real-world networks, communities can be
reflected by abundant node attributes with the fusion of graph topology. In
attribute-aware community detection, probabilistic generative models (PGMs)
have become the mainstream fusion method due to their principled
characterization and interpretation. Here, we propose a novel PGM without
imposing any distributional assumptions on attributes, which is superior to
existing PGMs that require attributes to be categorical or Gaussian
distributed. Based on the famous block model of graph structure, our model
fuses the attribute by describing its effect on node popularity using an
additional term. To characterize the effect quantitatively, we analyze the
detectability of communities for the proposed model and then establish the
requirements of the attribute-popularity term, which leads to a new scheme for
the model selection problem in attribute-aware community detection. With the
model determined, an efficient algorithm is developed to estimate the
parameters and to infer the communities. The proposed method is validated from
two aspects. First, the effectiveness of our algorithm is theoretically
guaranteed by the detectability condition, whose correctness is verified by
numerical experiments on artificial graphs. Second, extensive experiments show
that our method outperforms the competing approaches on a variety of real-world
networks.Comment: other authors do not want to preprin
The substructure and halo population of the Double Cluster and Persei
In order to study the stellar population and possible substructures in the
outskirts of Double Cluster and Persei, we investigate using the
GAIA DR2 data a sky area of about 7.5 degrees in radius around the Double
Cluster cores. We identify member stars using various criteria, including their
kinematics (viz, proper motion), individual parallaxes, as well as photometric
properties. A total of 2186 member stars in the parameter space were identified
as members. Based on the spatial distribution of the member stars, we find an
extended halo structure of and Persei, about 6 - 8 times larger than
their core radii. We report the discovery of filamentary substructures
extending to about 200 pc away from the Double Cluster. The tangential
velocities of these distant substructures suggest that they are more likely to
be the remnants of primordial structures, instead of a tidally disrupted stream
from the cluster cores. Moreover, the internal kinematic analysis indicates
that halo stars seems to be experiencing a dynamic stretching in the RA
direction, while the impact of the core components is relatively negligible.
This work also suggests that the physical scale and internal motions of young
massive star clusters may be more complex than previously thought.Comment: 9 pagges, 9 figures, Accecpted to A&
Reinforcement learning based anti-jamming schedule in cyber-physical systems
In this paper, the security issue of cyber-physical systems is investigated, where the observation data is transmitted from a sensor to an estimator through wireless channels disturbed by an attacker. The failure of this data transmission occurs, when the sensor accesses the channel that happens to be attacked by the jammer. Since the system performance measured by the estimation error depends on whether the data transmission is a success, the problem of selecting the channel to alleviate the attack effect is studied. Moreover, the state of each channel is time-variant due to various factors, such as path loss and shadowing. Motivated by energy conservation, the problem of selecting the channel with the best state is also considered. With the help of cognitive radio technique, the sensor has the ability of selecting a sequence of channels dynamically. Based on this, the problem of selecting the channel is resolved by means of reinforcement learning to jointly avoid the attack and enjoy the channel with the best state. A corresponding algorithm is presented to obtain the sequence of channels for the sensor, and its effectiveness is proved analytically. Numerical simulations further verify the derived results
The Chocolate Chip Cookie Model: Dust Geometry of Milky-Way like Disk Galaxies
We present a new two-component dust geometry model, the \textit{Chocolate
Chip Cookie} model, where the clumpy nebular regions are embedded in a diffuse
stellar/ISM disk, like chocolate chips in a cookie. By approximating the
binomial distribution of the clumpy nebular regions with a continuous Gaussian
distribution and omitting the dust scattering effect, our model solves the dust
attenuation process for both the emission lines and stellar continua via
analytical approaches. Our Chocolate Chip Cookie model successfully fits the
inclination dependence of both the effective dust reddening of the stellar
components derived from stellar population synthesis and that of the emission
lines characterized by the Balmer decrement for a large sample of Milky-Way
like disk galaxies selected from the main galaxy sample of the Sloan Digital
Sky Survey (SDSS). Our model shows that the clumpy nebular disk is about 0.55
times thinner and 1.6 times larger than the stellar disk for MW-like galaxies,
whereas each clumpy region has a typical optical depth in band. After considering the aperture effect, our model prediction
on the inclination dependence of dust attenuation is also consistent with
observations. Not only that, in our model, the dust attenuation curve of the
stellar population naturally depends on inclination and its median case is
consistent with the classical Calzetti law. Since the modelling constraints are
from the optical wavelengths, our model is unaffected by the optically thick
dust component, which however could bias the model's prediction of the infrared
emissions.Comment: 27 pages, 11 figures, 1 tabl
The morphological dependent Tully-Fisher relation of spiral galaxies
The Tully-Fisher relation of spiral galaxies shows notable dependence on
morphological types, with earlier type spirals having systematically lower
luminosity at fixed maximum rotation velocity . This decrement of
luminosity is more significant in shorter wavelengths. By modeling the rotation
curve and stellar population of different morphological type spiral galaxies in
combination, we find the of spiral galaxies is weakly dependent on
the morphological type, whereas the difference of the stellar population
originating from the bulge disk composition effect mainly account for the
morphological type dependence of the Tully-Fisher relation.Comment: 8 pages, 3 figures, ApJ accepte
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