95,589 research outputs found
Polarized Fermi gases in asymmetric optical lattices
The zero-temperature phase diagrams of imbalanced two-species Fermi gases are
investigated in asymmetric optical lattices with arbitrary potential depths,
based on the exact spectrum instead of the Fermi-Hubbard model. We study the
effect of lattice potentials and atomic densities to the fully paired
Bardeen-Cooper-Schrieffer (BCS) state and particularly the
Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state. It is found that the increasing
lattice potential favors BCS at low densities because of the enhanced effective
coupling; whereas FFLO is favored at intermediate densities when the system
undergoes a dimensional crossover. Finally using local density approximation we
study the evolution of phase profile in the presence of external harmonic traps
by merely tuning the lattice potentials.Comment: 7 pages, 6 figures, published versio
On the asymptotic stability of wave equations coupled by velocities of anti-symmetric type
In this paper, we study the asymptotic stability of two wave equations
coupled by velocities of anti-symmetric type via only one damping. We adopt the
frequency domain method to prove that the system with smooth initial data is
logarithmically stable, provided that the coupling domain and the damping
domain intersect each other. Moreover, we show, by an example, that this
geometric assumption of the intersection is necessary for 1-D case
Counterexample to Equivalent Nodal Analysis for Voltage Stability Assessment
Existing literature claims that the L-index for voltage instability detection
is inaccurate and proposes an improved index quantifying voltage stability
through system equivalencing. The proposed stability condition is claimed to be
exact in determining voltage instability.We show the condition is incorrect
through simple arguments accompanied by demonstration on a two-bus system
counterexample.Comment: 3 pages, 3 figure
A Necessary Condition for Power Flow Insolvability in Power Distribution Systems with Distributed Generators
This paper proposes a necessary condition for power flow insolvability in
power distribution systems with distributed generators (DGs). We show that the
proposed necessary condition indicates the impending singularity of the
Jacobian matrix and the onset of voltage instability. We consider different
operation modes of DG inverters, e.g., constant-power and constant-current
operations, in the proposed method. A new index based on the presented
necessary condition is developed to indicate the distance between the current
operating point and the power flow solvability boundary. Compared to existing
methods, the operating condition-dependent critical loading factor provided by
the proposed condition is less conservative and is closer to the actual power
flow solution space boundary. The proposed method only requires the present
snapshots of voltage phasors to monitor the power flow insolvability and
voltage stability. Hence, it is computationally efficient and suitable to be
applied to a power distribution system with volatile DG outputs. The accuracy
of the proposed necessary condition and the index is validated by simulations
on a distribution test system with different DG penetration levels
A Note on -Clean Rings
A -ring is called (strongly) -clean if every element of is the
sum of a projection and a unit (which commute with each other). In this note,
some properties of -clean rings are considered. In particular, a new class
of -clean rings which called strongly --regular are introduced. It
is shown that is strongly --regular if and only if is
-regular and every idempotent of is a projection if and only if
is strongly regular with nil, and every idempotent of
is lifted to a central projection of In addition, the stable range
conditions of -clean rings are discussed, and equivalent conditions among
-rings related to -cleanness are obtained.Comment: 16 page
Partial Penalized Likelihood Ratio Test under Sparse Case
This work is concern with testing the low-dimensional parameters of interest
with divergent dimensional data and variable selection for the rest under the
sparse case. A consistent test via the partial penalized likelihood approach,
called the partial penalized likelihood ratio test statistic is derived, and
its asymptotic distributions under the null hypothesis and the local
alternatives of order are obtained under some regularity conditions.
Meanwhile, the oracle property of the partial penalized likelihood estimator
also holds. The proposed partial penalized likelihood ratio test statistic
outperforms the full penalized likelihood ratio test statistic in term of size
and power, and performs as well as the classical likelihood ratio test
statistic. Moreover, the proposed method obtains the variable selection results
as well as the p-values of testing. Numerical simulations and an analysis of
Prostate Cancer data confirm our theoretical findings and demonstrate the
promising performance of the proposed partial penalized likelihood in
hypothesis testing and variable selection.Comment: 26 pages, 3 figures,6 table
Asymptotic stability of wave equations coupled by velocities
This paper is devoted to study the asymptotic stability of wave equations
with constant coefficients coupled by velocities. By using Riesz basis
approach, multiplier method and frequency domain approach respectively, we find
the sufficient and necessary condition, that the coefficients satisfy, leading
to the exponential stability of the system. In addition, we give the optimal
decay rate in one dimensional case
Biosignal Analysis with Matching-Pursuit Based Adaptive Chirplet Transform
Chirping phenomena, in which the instantaneous frequencies of a signal change
with time, are abundant in signals related to biological systems. Biosignals
are non-stationary in nature and the time-frequency analysis is a viable tool
to analyze them. It is well understood that Gaussian chirplet function is
critical in describing chirp signals. Despite the theory of adaptive chirplet
transform (ACT) has been established for more than two decades and is well
accepted in the community of signal processing, application of ACT to
bio-/biomedical signal analysis is still quite limited, probably because that
the power of ACT, as an emerging tool for biosignal analysis, has not yet been
fully appreciated by the researchers in the field of biomedical engineering. In
this paper, we describe a novel ACT algorithm based on the "coarse-refinement"
scheme. Namely, the initial estimate of a chirplet is implemented with the
matching-pursuit (MP) algorithm and subsequently it is refined using the
expectation-maximization (EM) algorithm, which we coin as MPEM algorithm. We
emphasize the robustness enhancement of the algorithm in face of noise, which
is important to biosignal analysis, as they are usually embedded in strong
background noise. We then demonstrate the capability of our algorithm by
applying it to the analysis of representative biosignals, including visual
evoked potentials (bioelectrical signals), audible heart sounds and bat
ultrasonic echolocation signals (bioacoustic signals), and human speech. The
results show that the MPEM algorithm provides more compact representation of
signals under investigation and clearer visualization of their time-frequency
structures, indicating considerable promise of ACT in biosignal analysis. The
MATLAB code repository is hosted on GitHub for free download
(https://github.com/jiecui/mpact).Comment: 27 pages, 8 figure
Stochastic Configuration Networks Ensemble for Large-Scale Data Analytics
This paper presents a fast decorrelated neuro-ensemble with heterogeneous
features for large-scale data analytics, where stochastic configuration
networks (SCNs) are employed as base learner models and the well-known negative
correlation learning (NCL) strategy is adopted to evaluate the output weights.
By feeding a large number of samples into the SCN base models, we obtain a huge
sized linear equation system which is difficult to be solved by means of
computing a pseudo-inverse used in the least squares method. Based on the group
of heterogeneous features, the block Jacobi and Gauss-Seidel methods are
employed to iteratively evaluate the output weights, and a convergence analysis
is given with a demonstration on the uniqueness of these iterative solutions.
Experiments with comparisons on two large-scale datasets are carried out, and
the system robustness with respect to the regularizing factor used in NCL is
given. Results indicate that the proposed ensemble learning techniques have
good potential for resolving large-scale data modelling problems.Comment: 20 pages, 7 figures, 9 tables; this paper has been submitted to
Information Sciences for publication in December 2016, and accepted on July
3, 201
Framed Cord Algebra Invariant of Knots in
We generalize Ng's two-variable algebraic/combinatorial -th framed knot
contact homology for framed oriented knots in to knots in , and prove that the resulting knot invariant is the same as the framed
cord algebra of knots. Actually, our cord algebra has an extra variable, which
potentially corresponds to the third variable in Ng's three-variable knot
contact homology. Our main tool is Lin's generalization of the Markov theorem
for braids in to braids in . We conjecture that our
framed cord algebras are always finitely generated for non-local knots.Comment: 37 pages, 14 figure
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