Results 11 to 20 of about 84,618 (266)
A combined BP‐MF algorithm for wideband off‐grid DOA estimation with DP prior
Electronics Letters, 2022 Direction‐of‐arrival (DOA) estimation based on sparse Bayesian learning (SBL) framework has attracted extensive attention. The accuracy of on‐grid DOA estimation is restricted by the prescribed grid, while off‐grid approaches resolves the problem of grid
Mengge Li +3 more
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Tellus: Series A, Dynamic Meteorology and Oceanography, 2019 A common way to introduce physical processes into numerical models of the atmosphere is to call the parameterization at every grid point. This can lead to considerable errors.
J. Steppeler, J. Li, F. Fang, J. Zhu
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Multidimensional Hierarchical Interpolation Method on Sparse Grids for the Absorption Problem
IEEE Access, 2019 The numerical integration of multidimensional functions using some variables of the sparse grid method for the absorption problem is presented in this paper.
Xuesong Chen, Heng Mai, Lili Zhang
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Sparse grid distance transforms
Graphical Models, 2010 We present a Sparse Grid Distance Transform (SGDT), an algorithm for computing and storing large distance fields. Although SGDT is based on a divide-and-conquer algorithm for distance transforms, its data structure is quite simplified. Our observations revealed that distance fields can be recovered from distance fields of sub-block cluster boundaries ...
Takashi Michikawa, Hiromasa Suzuki
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An Efficient and Fast Sparse Grid Algorithm for High-Dimensional Numerical Integration
Mathematics, 2023 This paper is concerned with developing an efficient numerical algorithm for the fast implementation of the sparse grid method for computing the d-dimensional integral of a given function.
Huicong Zhong, Xiaobing Feng
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Shear turbulence on a sparse spectral grid [PDF]
Physical Review E, 2007 We simulate turbulence in a plane Couette geometry by a spectral method intermediate between full resolution and the complete elimination of small modes common in large eddy simulations. The wave number grid is sparse in spanwise and downstream direction, with a total number of modes proportional to Re(3/4) lnRe.
F, De Lillo, Bruno, Eckhardt
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Remote Sensing, 2018 In recent years, the development of compressed sensing (CS) and array signal processing provides us with a broader perspective of 3D imaging. The CS-based imaging algorithms have a better performance than traditional methods.
Zekun Jiao +4 more
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Adaptive Sparse Grid Classification Using Grid Environments [PDF]
, 2007 Common techniques tackling the task of classification in data mining employ ansatz functions associated to training data points to fit the data as well as possible. Instead, the feature space can be discretized and ansatz functions centered on grid points can be used.
Dirk Pflüger +2 more
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Off-Grid DOA Estimation Using Alternating Block Coordinate Descent in Compressed Sensing
Sensors, 2015 This paper presents a novel off-grid direction of arrival (DOA) estimation method to achieve the superior performance in compressed sensing (CS), in which DOA estimation problem is cast as a sparse reconstruction.
Weijian Si, Xinggen Qu, Zhiyu Qu
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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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