Results 31 to 40 of about 14,098 (299)
A Multiple Target Localization with Sparse Information in Wireless Sensor Networks
International Journal of Distributed Sensor Networks, 2016 It is a great challenge for wireless sensor network to provide enough information for targets localization due to the limits on application environment and its nature, such as energy, communication, and sensing precision.
Liping Liu +3 more
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Sparse Grids for the Vlasov–Poisson Equation [PDF]
, 2016 The Vlasov–Poisson equation models the evolution of a plasma in an external or self-consistent electric field. The model consists of an advection equation in six dimensional phase space coupled to Poisson’s equation. Due to the high dimensionality and the development of small structures the numerical solution is quite challenging.
Kormann, K., Sonnendrücker, E.
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Sparse grid quadrature on products of spheres [PDF]
Numerical Algorithms, 2015 We examine sparse grid quadrature on weighted tensor products (WTP) of reproducing kernel Hilbert spaces on products of the unit sphere, in the case of worst case quadrature error for rules with arbitrary quadrature weights. We describe a dimension adaptive quadrature algorithm based on an algorithm of Hegland (2003), and also formulate a version of ...
Markus Hegland, Paul C. Leopardi
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4th Workshop on Sparse Grids and Applications [PDF]
, 2018 Sparse grids are a popular tool for the numerical treatment of high-dimensional problems. Where classical numerical discretization schemes fail in more than three or four dimensions, sparse grids, in their different flavors, are frequently the method of ...
Webster, Clayton +3 more
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On the dispersion of sparse grids
Journal of Complexity, 2018 For any natural number $d$ and positive number $\varepsilon$, we present a point set in the $d$-dimensional unit cube $[0,1]^d$ that intersects every axis-aligned box of volume greater than $\varepsilon$. These point sets are very easy to handle and in a vast range for $\varepsilon$ and $d$, we do not know any smaller set with this property.
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Fast deconvolved beamforming for arbitrary arrays based on off-grid sparse Bayesian learning [PDF]
JASA Express LettersThe deconvolved beamforming (dCv) improves spatial resolution without expanding the array aperture but fails for the shift-variant beam pattern and the real targets, which are not located on the sampling grids.
Jianli Huang +5 more
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Adaptive Sparse Grids in Reinforcement Learning [PDF]
, 2022 179194We propose a model-based online reinforcement learning approach for continuous domains with deterministic transitions using a spatially adaptive sparse grid in the planning stage.
Klompmaker, Irene, Garcke, Jochen
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Orthogonal polynomial expansions on sparse grids
Journal of Complexity, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yanzhao Cao +2 more
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Sensors, 2017 In this paper a two-phase compressive sensing (CS) and received signal strength (RSS)-based target localization approach is proposed to improve position accuracy by dealing with the unknown target population and the effect of grid dimensions on position ...
Jun Yan +3 more
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Finite Differences on Sparse Grids for Continuous-Time Heterogeneous Agent Models
AlgorithmsWe present a finite difference method working on sparse grids to solve higher dimensional heterogeneous agent models. If one wants to solve the arising Hamilton–Jacobi–Bellman equation on a standard full grid, one faces the problem that the number of ...
Jochen Garcke, Steffen Ruttscheidt
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