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Quasi-randomized path planning

Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), 2002
We propose the use of quasi-random sampling techniques for path planning in high-dimensional configuration spaces. Following similar trends from related numerical computation fields, we show several advantages offered by these techniques in comparison to random sampling.
Michael S. Branicky   +3 more
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Quasi‐random classes of hypergraphs

Random Structures & Algorithms, 1990
AbstractWe investigate the relations among a number of different graph properties for k‐uniformhypergraphs, which are shared by random hypergraphs. Various graph properties form equivalence classes which in turn constitute a natural hierarchy. The analogues for binary functions on k‐tuples and for hypergraphs with small density are also considered ...
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Weak quasi‐randomness for uniform hypergraphs

Random Structures & Algorithms, 2011
AbstractWe study quasi‐random properties of k‐uniform hypergraphs. Our central notion is uniform edge distribution with respect to large vertex sets. We will find several equivalent characterisations of this property and our work can be viewed as an extension of the well known Chung‐Graham‐Wilson theorem for quasi‐random graphs.Moreover, let Kk be the ...
David Conlon   +3 more
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Quasi-Random Multimetallic Nanoparticle Arrays

ACS Nano, 2023
This paper describes a nanofabrication procedure that can generate multiscale substrates with quasi-random microregions of nanoparticle arrays having different periodicities and metals. We combine cycles of large-area nanoparticle array fabrication with solvent-assisted wrinkle lithography to mask and etch quasi-random areas of prefabricated ...
Francisco Freire-Fernández   +7 more
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Quasi-random points keep their distance

Mathematics and Computers in Simulation, 2007
For a given net, composed of \(N\) quasi-random points \(Q_{0}, Q_{1}, \dots , Q_{N-1}\) in the \(n\)-dimensional hypercube \(I^{n}\), the measure \(d_{N} = \min_{0 \leq i < j < N} \rho(Q_{i}, Q_{j}), \) where \(\rho\) is the Euclidean distance between the points \(Q_{i}\) and \(Q_{j},\) called minimum distance, is considered. In section 2 the behavior
Ilya M. Sobol, Boris Shukhman
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Self-Organization of Quasi-Random Copolymers

Doklady Physical Chemistry, 2002
The theory of integral RISM-equations is applied to describe the equilibrium structure of a quasi random protein-like polymer. Interaction of collective correlation functions is given by the Ornstein-Zernike nonlinear integral equation.
Zherenkova, L. V.   +3 more
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Book Ramsey Numbers and Quasi-Randomness

Combinatorics, Probability and Computing, 2005
A book \(B_p\) with \(p\) pages is a graph consisting of \(p\) triangles sharing a common edge. It was shown by \textit{C. C. Rousseau} and \textit{J. Sheehan} in [J. Graph Theory 2, 77--87 (1978; Zbl 0377.05033)] that the Ramsey number \(r(B_n, B_n) = (4 + o(1))n\).
Nikiforov, V.   +2 more
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Regularity lemmas for hypergraphs and quasi‐randomness

Random Structures & Algorithms, 1991
AbstractWe give a simple proof for Szemerédi's Regularity Lemma and its generalization for k‐uniform hypergraphs. For fixed k, there are altogether k ‐1 different versions of the regularity lemma for k‐uniform hypergraphs. The connection between regularity lemmas for hypergraphs and quasi‐random classes of hypergraphs is also investigated.
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Remarks on randomization of quasi-random numbers

Monte Carlo Methods and Applications, 2018
Abstract In this paper we discuss estimation of the quasi-Monte Carlo methods error in the case of calculation of high-order integrals. Quasi-random Halton sequences are considered as a special case. Randomization of these sequences by the random shift method turns out to lead to well-known random quadrature formulas with one free node ...
Sergej M. Ermakov, Svetlana N. Leora
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Quasi-random nonlinear scale space

Pattern Recognition Letters, 2010
A novel nonlinear scale space framework is proposed for the purpose of multi-scale image representation. The scale space decomposition problem is formulated as a general Bayesian least-squares estimation problem. A quasi-random density estimation approach is introduced for estimating the posterior distribution between consecutive scale space ...
Akshaya Kumar Mishra   +3 more
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