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Numerical experiments
, 2004
"... Kuramoto–Sivashinsky equation Allen–Cahn equation Korteweg de Vries equation Nonlinear Schrödinger equation ..."
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Kuramoto–Sivashinsky equation Allen–Cahn equation Korteweg de Vries equation Nonlinear Schrödinger equation
Numerical experiments in homogeneous turbulence
 Available from NASA Scienti & Technical Information (help@sti.nasa.gov
, 1981
"... i/ ..."
The RungeKutta discontinuous Galerkin method for conservation laws V: multidimensional systems
, 1997
"... This is the fifth paper in a series in which we construct and study the socalled RungeKutta Discontinuous Galerkin method for numerically solving hyperbolic conservation laws. In this paper, we extend the method to multidimensional nonlinear systems of conservation laws. The algorithms are describ ..."
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Cited by 508 (44 self)
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are described and discussed, including algorithm formulation and practical implementation issues such as the numerical fluxes, quadrature rules, degrees of freedom, and the slope limiters, both in the triangular and the rectangular element cases. Numerical experiments for two dimensional Euler equations
Numerical Experiments in String Cosmology
 Nucl. Phys. B468 319 [hepth/9511075
, 1996
"... We investigate some classical aspects of fundamental strings via numerical experiments. In particular, we study the thermodynamics of a string network within a toroidal universe, as a function of string energy density and space dimensionality. We find that when the energy density of the system is lo ..."
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Cited by 17 (0 self)
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We investigate some classical aspects of fundamental strings via numerical experiments. In particular, we study the thermodynamics of a string network within a toroidal universe, as a function of string energy density and space dimensionality. We find that when the energy density of the system
Compressed sensing
, 2004
"... We study the notion of Compressed Sensing (CS) as put forward in [14] and related work [20, 3, 4]. The basic idea behind CS is that a signal or image, unknown but supposed to be compressible by a known transform, (eg. wavelet or Fourier), can be subjected to fewer measurements than the nominal numbe ..."
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Cited by 3625 (22 self)
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norm. We perform a series of numerical experiments which validate in general terms the basic idea proposed in [14, 3, 5], in the favorable case where the transform coefficients are sparse in the strong sense that the vast majority are zero. We then consider a range of lessfavorable cases, in which
The R*tree: an efficient and robust access method for points and rectangles
 INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA
, 1990
"... The Rtree, one of the most popular access methods for rectangles, is based on the heuristic optimization of the area of the enclosing rectangle in each inner node. By running numerous experiments in a standardized testbed under highly varying data, queries and operations, we were able to design the ..."
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Cited by 1262 (74 self)
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The Rtree, one of the most popular access methods for rectangles, is based on the heuristic optimization of the area of the enclosing rectangle in each inner node. By running numerous experiments in a standardized testbed under highly varying data, queries and operations, we were able to design
Numerical Experiments with Symmetric Eigensolvers
, 1998
"... This report describes and analyzes numerical experiments carried out with various symmetric eigensolvers in the context of the material science code Wien 97. Of particular interest are the performance improvements achieved with a new Level 3 eigensolver. The techniques which lead to a significant sp ..."
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This report describes and analyzes numerical experiments carried out with various symmetric eigensolvers in the context of the material science code Wien 97. Of particular interest are the performance improvements achieved with a new Level 3 eigensolver. The techniques which lead to a significant
Decoding by Linear Programming
, 2004
"... This paper considers the classical error correcting problem which is frequently discussed in coding theory. We wish to recover an input vector f ∈ Rn from corrupted measurements y = Af + e. Here, A is an m by n (coding) matrix and e is an arbitrary and unknown vector of errors. Is it possible to rec ..."
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Cited by 1399 (16 self)
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for some ρ> 0. In short, f can be recovered exactly by solving a simple convex optimization problem (which one can recast as a linear program). In addition, numerical experiments suggest that this recovery procedure works unreasonably well; f is recovered exactly even in situations where a significant
Results 1  10
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805,152