29,960 research outputs found
Multiscale approach for the network compression-friendly ordering
We present a fast multiscale approach for the network minimum logarithmic
arrangement problem. This type of arrangement plays an important role in a
network compression and fast node/link access operations. The algorithm is of
linear complexity and exhibits good scalability which makes it practical and
attractive for using on large-scale instances. Its effectiveness is
demonstrated on a large set of real-life networks. These networks with
corresponding best-known minimization results are suggested as an open
benchmark for a research community to evaluate new methods for this problem
An adaptive grid refinement strategy for the simulation of negative streamers
The evolution of negative streamers during electric breakdown of a
non-attaching gas can be described by a two-fluid model for electrons and
positive ions. It consists of continuity equations for the charged particles
including drift, diffusion and reaction in the local electric field, coupled to
the Poisson equation for the electric potential. The model generates field
enhancement and steep propagating ionization fronts at the tip of growing
ionized filaments. An adaptive grid refinement method for the simulation of
these structures is presented. It uses finite volume spatial discretizations
and explicit time stepping, which allows the decoupling of the grids for the
continuity equations from those for the Poisson equation. Standard refinement
methods in which the refinement criterion is based on local error monitors fail
due to the pulled character of the streamer front that propagates into a
linearly unstable state. We present a refinement method which deals with all
these features. Tests on one-dimensional streamer fronts as well as on
three-dimensional streamers with cylindrical symmetry (hence effectively 2D for
numerical purposes) are carried out successfully. Results on fine grids are
presented, they show that such an adaptive grid method is needed to capture the
streamer characteristics well. This refinement strategy enables us to
adequately compute negative streamers in pure gases in the parameter regime
where a physical instability appears: branching streamers.Comment: 46 pages, 19 figures, to appear in J. Comp. Phy
High Quality Image Interpolation via Local Autoregressive and Nonlocal 3-D Sparse Regularization
In this paper, we propose a novel image interpolation algorithm, which is
formulated via combining both the local autoregressive (AR) model and the
nonlocal adaptive 3-D sparse model as regularized constraints under the
regularization framework. Estimating the high-resolution image by the local AR
regularization is different from these conventional AR models, which weighted
calculates the interpolation coefficients without considering the rough
structural similarity between the low-resolution (LR) and high-resolution (HR)
images. Then the nonlocal adaptive 3-D sparse model is formulated to regularize
the interpolated HR image, which provides a way to modify these pixels with the
problem of numerical stability caused by AR model. In addition, a new
Split-Bregman based iterative algorithm is developed to solve the above
optimization problem iteratively. Experiment results demonstrate that the
proposed algorithm achieves significant performance improvements over the
traditional algorithms in terms of both objective quality and visual perceptionComment: 4 pages, 5 figures, 2 tables, to be published at IEEE Visual
Communications and Image Processing (VCIP) 201
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