16,899 research outputs found
Theory of the quasiparticle excitation in high T cuprates: quasiparticle charge and nodal-antinodal dichotomy
A variational theory is proposed for the quasiparticle excitation in high
T cuprates. The theory goes beyond the usual Gutzwiller projected mean
field state description by including the spin-charge recombination effect in
the RVB background. The spin-charge recombination effect is found to
qualitatively alter the behavior of the quasiparticle charge as a function of
doping and cause considerable anisotropy in quasiparticle weight on the Fermi
surface.Comment: 10 page
Multiple testing via for large-scale imaging data
The multiple testing procedure plays an important role in detecting the
presence of spatial signals for large-scale imaging data. Typically, the
spatial signals are sparse but clustered. This paper provides empirical
evidence that for a range of commonly used control levels, the conventional
procedure can lack the ability to detect statistical
significance, even if the -values under the true null hypotheses are
independent and uniformly distributed; more generally, ignoring the neighboring
information of spatially structured data will tend to diminish the detection
effectiveness of the procedure. This paper first
introduces a scalar quantity to characterize the extent to which the "lack of
identification phenomenon" () of the
procedure occurs. Second, we propose a new multiple comparison procedure,
called , to accommodate the spatial information of
neighboring -values, via a local aggregation of -values. Theoretical
properties of the procedure are investigated under weak
dependence of -values. It is shown that the
procedure alleviates the of the
procedure, thus substantially facilitating the selection of more stringent
control levels. Simulation evaluations indicate that the procedure improves the detection sensitivity of the procedure with little loss in detection specificity. The computational
simplicity and detection effectiveness of the procedure
are illustrated through a real brain fMRI dataset.Comment: Published in at http://dx.doi.org/10.1214/10-AOS848 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Resource Allocation for Delay Differentiated Traffic in Multiuser OFDM Systems
Most existing work on adaptive allocation of subcarriers and power in
multiuser orthogonal frequency division multiplexing (OFDM) systems has focused
on homogeneous traffic consisting solely of either delay-constrained data
(guaranteed service) or non-delay-constrained data (best-effort service). In
this paper, we investigate the resource allocation problem in a heterogeneous
multiuser OFDM system with both delay-constrained (DC) and
non-delay-constrained (NDC) traffic. The objective is to maximize the sum-rate
of all the users with NDC traffic while maintaining guaranteed rates for the
users with DC traffic under a total transmit power constraint. Through our
analysis we show that the optimal power allocation over subcarriers follows a
multi-level water-filling principle; moreover, the valid candidates competing
for each subcarrier include only one NDC user but all DC users. By converting
this combinatorial problem with exponential complexity into a convex problem or
showing that it can be solved in the dual domain, efficient iterative
algorithms are proposed to find the optimal solutions. To further reduce the
computational cost, a low-complexity suboptimal algorithm is also developed.
Numerical studies are conducted to evaluate the performance the proposed
algorithms in terms of service outage probability, achievable transmission rate
pairs for DC and NDC traffic, and multiuser diversity.Comment: 29 pages, 8 figures, submitted to IEEE Transactions on Wireless
Communication
Compressed Sensing Based on Random Symmetric Bernoulli Matrix
The task of compressed sensing is to recover a sparse vector from a small
number of linear and non-adaptive measurements, and the problem of finding a
suitable measurement matrix is very important in this field. While most recent
works focused on random matrices with entries drawn independently from certain
probability distributions, in this paper we show that a partial random
symmetric Bernoulli matrix whose entries are not independent, can be used to
recover signal from observations successfully with high probability. The
experimental results also show that the proposed matrix is a suitable
measurement matrix.Comment: arXiv admin note: text overlap with arXiv:0902.4394 by other author
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