842 research outputs found
Constraints of the equation of state of dark energy from current and future observational data by piecewise parametrizations
The model-independent piecewise parametrizations (0-spline, linear-spline and
cubic-spline) are used to estimate constraints of equation of state of dark
energy () from current observational data (including SNIa, BAO and
Hubble parameter) and the simulated future data. A combination of fitting
results of from these three spline methods reveal essential properties
of real equation of state . It is shown that beyond redshift
is poorly constrained from current data, and the mock future
supernovae data give poor constraints of beyond .
The fitting results also indicate that there might exist a rapid transition of
around . The difference between three spline methods in
reconstructing and constraining has also been discussed.Comment: 16 pages, 2 figures, 5 table
Dirac series for
Up to equivalence, this paper classifies all the irreducible unitary
representations with non-zero Dirac cohomology for the simple Lie group
, which is of Hermitian symmetric type. Each FS-scattered Dirac
series of is realized as a composition factor of certain
module. Along the way, we have also obtained all
the fully supported irreducible unitary representations of with
integral infinitesimal characters.Comment: 32 pages, some strings are folde
Hierarchical Codebook Design for Beamforming Training in Millimeter-Wave Communication
In millimeter-wave communication, large antenna arrays are required to
achieve high power gain by steering towards each other with narrow beams, which
poses the problem to efficiently search the best beam direction in the angle
domain at both Tx and Rx sides. As the exhaustive search is time consuming,
hierarchical search has been widely accepted to reduce the complexity, and its
performance is highly dependent on the codebook design. In this paper, we
propose two basic criteria for the hierarchical codebook design, and devise an
efficient hierarchical codebook by jointly exploiting sub-array and
deactivation (turning-off) antenna processing techniques, where closed-form
expressions are provided to generate the codebook. Performance evaluations are
conducted under different system and channel models. Results show superiority
of the proposed codebook over the existing alternatives.Comment: 13 pages, 11 figures. To appear in IEEE Trans. Wireless Commn. This
paper proposes the BMW-SS approach to design a fully-hierarchical codebook
for mmWave communication
IRCI Free Colocated MIMO Radar Based on Sufficient Cyclic Prefix OFDM Waveforms
In this paper, we propose a cyclic prefix (CP) based MIMO-OFDM range
reconstruction method and its corresponding MIMO-OFDM waveform design for
co-located MIMO radar systems. Our proposed MIMO-OFDM waveform design achieves
the maximum signal-to-noise ratio (SNR) gain after the range reconstruction and
its peak-to-average power ratio (PAPR) in the discrete time domain is also
optimal, i.e., 0dB, when Zadoff-Chu sequences are used in the discrete
frequency domain as the weighting coefficients for the subcarriers. We also
investigate the performance when there are transmit and receive digital
beamforming (DBF) pointing errors. It is shown that our proposed CP based
MIMO-OFDM range reconstruction is inter-range-cell interference (IRCI) free no
matter whether there are transmit and receive DBF pointing errors or not.
Simulation results are presented to verify the theory and compare it with the
conventional OFDM and LFM co-located MIMO radars.Comment: 27 pages, 11 figure
A wavelet frame coefficient total variational model for image restoration
In this paper, we propose a vector total variation (VTV) of feature image
model for image restoration. The VTV imposes different smoothing powers on
different features (e.g. edges and cartoons) based on choosing various
regularization parameters. Thus, the model can simultaneously preserve edges
and remove noises. Next, the existence of solution for the model is proved and
the split Bregman algorithm is used to solve the model. At last, we use the
wavelet filter banks to explicitly define the feature operator and present some
experimental results to show its advantage over the related methods in both
quality and efficiency.Comment: 19 pages, 8 figures, 2 table
Some aspects of QGP phase in a hQCD model
We continue to study the holographic QCD (hQCD) model, proposed in a previous
paper, in an Einstein-Maxwell-Dilaton (EMD) system. In this paper we discuss
some aspects of quark gluon plasma (QGP) in the hQCD model, such as drag force,
jet quenching parameter and screening length. The results turn out to be
consistent with those as expected in QCD qualitatively. By calculating free
energy of the background black hole solution, we find that there exists a
Hawking-Page phase transition between small black hole and big black hole when
chemical potential is less than a critical one , and the phase
transition is absent when chemical potential is beyond the critical one.Comment: 31 pages,15 figures, LaTeX, Statements and figures have been
improved. Accepted by JHE
A Holographic Study on Vector Condensate Induced by a Magnetic Field
We study a holographic model with vector condensate by coupling the anti-de
Sitter gravity to an Abelian gauge field and a charged vector field in
dimensional spacetime. In this model there exists a non-minimal coupling of the
vector filed to the gauge field. We find that there is a critical temperature
below which the charged vector condenses via a second order phase transition.
The DC conductivity becomes infinite and the AC conductivity develops a gap in
the condensed phase. We study the effect of a background magnetic field on the
system. It is found that the background magnetic field can induce the
condensate of the vector field even in the case without chemical
potential/charge density. In the case with non-vanishing charge density, the
transition temperature raises with the applied magnetic field, and the
condensate of the charged vector operator forms a vortex lattice structure in
the spatial directions perpendicular to the magnetic field.Comment: v3: minor changes, references added, to appear in JHE
Holographic Entanglement Entropy in Insulator/Superconductor Transition
We investigate the behaviors of entanglement entropy in the holographical
insulator/superconductor phase transition. We calculate the holographic
entanglement entropy for two kinds of geometry configurations in a completely
back-reacted gravitational background describing the insulator/superconductor
phase transition. The non-monotonic behavior of the entanglement entropy is
found in this system. In the belt geometry case, there exist four phases
characterized by the chemical potential and belt width.Comment: v2: 18 pages, 12 figures, references and figures added, minor
corrections mad
OPARC: Optimal and Precise Array Response Control Algorithm -- Part II: Multi-points and Applications
In this paper, the optimal and precise array response control (OPARC)
algorithm proposed in Part I of this two paper series is extended from single
point to multi-points. Two computationally attractive parameter determination
approaches are provided to maximize the array gain under certain constraints.
In addition, the applications of the multi-point OPARC algorithm to array
signal processing are studied. It is applied to realize array pattern synthesis
(including the general array case and the large array case), multi-constraint
adaptive beamforming and quiescent pattern control, where an innovative concept
of normalized covariance matrix loading (NCL) is proposed. Finally, simulation
results are presented to validate the superiority and effectiveness of the
multi-point OPARC algorithm.Comment: submitted to TS
Locality Constraint Dictionary Learning with Support Vector for Pattern Classification
Discriminative dictionary learning (DDL) has recently gained significant
attention due to its impressive performance in various pattern classification
tasks. However, the locality of atoms is not fully explored in conventional DDL
approaches which hampers their classification performance. In this paper, we
propose a locality constraint dictionary learning with support vector
discriminative term (LCDL-SV), in which the locality information is preserved
by employing the graph Laplacian matrix of the learned dictionary. To jointly
learn a classifier during the training phase, a support vector discriminative
term is incorporated into the proposed objective function. Moreover, in the
classification stage, the identity of test data is jointly determined by the
regularized residual and the learned multi-class support vector machine.
Finally, the resulting optimization problem is solved by utilizing the
alternative strategy. Experimental results on benchmark databases demonstrate
the superiority of our proposed method over previous dictionary learning
approaches on both hand-crafted and deep features. The source code of our
proposed LCDL-SV is accessible at https://github.com/yinhefeng/LCDL-SVComment: submitted to IEEE Acces
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