24,980 research outputs found
GMM-Based Hidden Markov Random Field for Color Image and 3D Volume Segmentation
In this project, we first study the Gaussian-based hidden Markov random field
(HMRF) model and its expectation-maximization (EM) algorithm. Then we
generalize it to Gaussian mixture model-based hidden Markov random field. The
algorithm is implemented in MATLAB. We also apply this algorithm to color image
segmentation problems and 3D volume segmentation problems
HMRF-EM-image: Implementation of the Hidden Markov Random Field Model and its Expectation-Maximization Algorithm
In this project, we study the hidden Markov random field (HMRF) model and its
expectation-maximization (EM) algorithm. We implement a MATLAB toolbox named
HMRF-EM-image for 2D image segmentation using the HMRF-EM framework. This
toolbox also implements edge-prior-preserving image segmentation, and can be
easily reconfigured for other problems, such as 3D image segmentation.Comment: This work originally appears as the final project of Prof. Birsen
Yazici's course Detection and Estimation Theory at RP
Non-flow, and what flow to subtract in jet-correlation
We derive analytical forms for non-flow contributions from cluster
correlation to two-particle elliptic flow (v2{2}) measure. We also derive an
analytical form for jet-correlation flow-background with the same cluster
approach. We argue that the elliptic flow v2 parameter to be used in
jet-correlation background is that from two-particle method excluding non-flow
correlations unrelated to the reaction plane, but including cross-terms between
cluster correlation and cluster flow. We verify our result with Monte Carlo
simulations. We discuss how one may obtain the v2 parameter for jet-correlation
background experimentally.Comment: 11 pages 1 table 1 figure. Proceedings of 4th international workshop
on High-pT physics at LHC-09, 2009, Prague, Czech Republi
Dynamic bifurcation and instability of Dean problem
The main objective of this paper is to address the instability and dynamical
bifurcation of the Dean problem. A nonlinear theory is obtained for the Dean
problem, leading in particular to rigorous justifications of the linear theory
used by physicists, and the vortex structure. The main technical tools are the
dynamic bifurcation theory [15] developed recently by Ma and Wang.Comment: 16 pages,1figur
Multiply Warped Products with a Quarter-symmetric Connection
In this paper, we study the Einstein warped products and multiply warped
products with a quarter-symmetric connection. We also study warped products and
multiply warped products with a quarter-symmetric connection with constant
scalar curvature. Then apply our results to generalized Robertson-Walker
spacetimes with a quarter-symmetric connection and generalized Kasner
space-times with a quarter-symmetric connection.Comment: 41 pages. arXiv admin note: text overlap with arXiv:1207.509
Influence of inelastic relaxation time on intrinsic spin Hall effects in a disordered two-dimensional electron gas
The influence of inelastic relaxation time on the intrinsic spin Hall effects
in a disordered two-dimensional electron gas with Rashba interaction is
studied, which clarifies the controversy of impurity effects in the system. We
reveal that, due to the existence of inelastic scattering, the spin Hall
conductivity does not vanish when the impurity concentration diminishes to zero
no matter it is non-magnetically or magnetically disordered. The spin
accumulation is evaluated by using the obtained spin Hall conductivity, and an
alternate route is suggested to verify the intrinsic spin Hall effect by
measuring the spin accumulation at different ratios.Comment: Revtex 6 pages, 1 figure, extended with more detail
Probing the excited-state quantum phase transition through statistics of Loschmidt echo and quantum work
By analyzing the probability distributions of the Loschmidt echo (LE) and
quantum work, we examine the nonequilibrium effects of a quantum many-body
system, which exhibits an excited-state quantum phase transition (ESQPT).
We find that depending on the value of the controlling parameter the
distribution of the LE displays different patterns.
At the critical point of the ESQPT, both the averaged LE and the averaged
work show a cusplike shape.
Furthermore, by employing the finite-size scaling analysis of the averaged
work, we obtain the critical exponent of the ESQPT.
Finally, we show that at the critical point of ESQPT the eigenstate is a
highly localized state, further highlighting the influence of the ESQPT on the
properties of the many-body system.Comment: 10 pages, 13 figures; accepted for publication in Physical Review
Half-arc-transitive graphs of prime-cube order of small valencies
A graph is called {\em half-arc-transitive} if its full automorphism group
acts transitively on vertices and edges, but not on arcs. It is well known that
for any prime there is no tetravalent half-arc-transitive graph of order
or . Xu~[Half-transitive graphs of prime-cube order, J. Algebraic
Combin. 1 (1992) 275-282] classified half-arc-transitive graphs of order
and valency . In this paper we classify half-arc-transitive graphs of order
and valency or . In particular, the first known infinite family of
half-arc-transitive Cayley graphs on non-metacyclic -groups is constructed.Comment: 13 page
Feature Learning by Multidimensional Scaling and its Applications in Object Recognition
We present the MDS feature learning framework, in which multidimensional
scaling (MDS) is applied on high-level pairwise image distances to learn
fixed-length vector representations of images. The aspects of the images that
are captured by the learned features, which we call MDS features, completely
depend on what kind of image distance measurement is employed. With properly
selected semantics-sensitive image distances, the MDS features provide rich
semantic information about the images that is not captured by other feature
extraction techniques. In our work, we introduce the iterated
Levenberg-Marquardt algorithm for solving MDS, and study the MDS feature
learning with IMage Euclidean Distance (IMED) and Spatial Pyramid Matching
(SPM) distance. We present experiments on both synthetic data and real images
--- the publicly accessible UIUC car image dataset. The MDS features based on
SPM distance achieve exceptional performance for the car recognition task.Comment: To appear in SIBGRAPI 201
Bipartite bi-Cayley graphs over metacyclic groups of odd prime-power order
A graph is a bi-Cayley graph over a group if is a
semiregular group of automorphisms of having two orbits. Let be a
non-abelian metacyclic -group for an odd prime , and let be a
connected bipartite bi-Cayley graph over the group . In this paper, we prove
that is normal in the full automorphism group of
when is a Sylow -subgroup of . As an
application, we classify half-arc-transitive bipartite bi-Cayley graphs over
the group of valency less than . Furthermore, it is shown that there
are no semisymmetric and no arc-transitive bipartite bi-Cayley graphs over the
group of valency less than .Comment: 20 pages, 1 figur
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