作者：
YANG Ju'e HU Qiya YU DehaoLSEC
Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100080 China
In this paper, we introduce a domain decomposition method with non-matching grids for solving Dirichlet exterior boundary problems by coupling of finite element method （FEM） and natural boundary element method（BEM...
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In this paper, we introduce a domain decomposition method with non-matching grids for solving Dirichlet exterior boundary problems by coupling of finite element method （FEM） and natural boundary element method（BEM）. We first derive the optimal energy error estimate of the nonconforming approximation generated by this method. Then we apply a Dirichlet-Neumann（D-N） alternating algorithm to solve the coupled discrete system. It will be shown that such iterative method possesses the optimal convergence. The numerical experiments testify our theoretical results.
The phase noise suppression methods applied on the interferogram of Interferometric synthetic aperture radar (InSAR) are studied. Filtering phase noise in an interferogram is an important aspect in InSAR data processi...
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The phase noise suppression methods applied on the interferogram of Interferometric synthetic aperture radar (InSAR) are studied. Filtering phase noise in an interferogram is an important aspect in InSAR data processing. But any improper altering of the wrapped phase may influence the quality of derived DEM because the interferometric phase contains the topographic information. Therefore, one of the difficulties in phase noise filtering is how to remove the noise and preserve the spatial resolution effectively. In this paper, a new adaptive approach based on the nonlinear anisotropic diffusion equation is presented for removing the noise in the interferogram. The key idea is that for low gradients, isotropic smoothing is performed, and for high gradient, smoothing is only applied in the direction of the isophote and not across it. During the course of noise suppressing, image features and their directions are extracted. Less smoothing is in the locations with strong image feature, and more smoothing in the locations with weak image feature;minimal smoothing in the directions across the image features, and maximal smoothing in the directions along the image features. At the end of this paper, this approach is compared with some existing approachs for InSAR noise filtering and the experimental results by processing Canada Radarsatl data are used to confirm that the method is more effective in suppressing noise in the interferogram.
By bianalytic functions, the boundary integral formula of the stress function for the elastic problem in a circle plane is developed. But this integral formula includes a strongly singular integral and can not be dire...
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By bianalytic functions, the boundary integral formula of the stress function for the elastic problem in a circle plane is developed. But this integral formula includes a strongly singular integral and can not be directly calculated. After the stress function is expounded to Fourier series, making use of some formulas in generalized functions to the convolutions, the boundary integral formula which does not include strongly singular integral is derived further. Then the stress function can be got simply by the integration of the values of the stress function and its derivative on the boundary. Some examples are given. It shows that the boundary integral formula of the stress function for the elastic problem is convenient.
A set of generalized symmetries with arbitrary functions of t for the Konopelchenko-Dubrovsky (KD)equation in 2+1 space dimensions is given by using a direct method called formal function series method presented by Lo...
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A set of generalized symmetries with arbitrary functions of t for the Konopelchenko-Dubrovsky (KD)equation in 2+1 space dimensions is given by using a direct method called formal function series method presented by Lou. These symmetries constitute an infinite-dimensional generalized w∞ algebra.
We study hybrid search schemes for unstructured peer-to-peer networks. We quantify performance in terms of number of hits, network overhead, and response time. Our schemes combine flooding and random walks, look ahead...
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The paper presents a new class of memory gradient methods with inexact line searches for unconstrained minimization problems. The methods use more previous iterative information than other methods to generate a search...
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In this paper, an efficient technique is proposed to optimize the geometie and arrangements of the slots of the CARLSAs. Moment method in carried out to obtain the unknown excitation coefficients after spliting the sl...
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In this paper, a new technique is proposed to analyse the mutual admittance between the slots of the radial line slot antennas (RLSA). No Green's functions are required since the mutual and self admittance of the ...
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Two kinds of algebraic multigrid (AMG) algorithms with three-dimensional equal algebraic structures are constructed on the basis of a two-dimensional coarsing technique. The AMG method and the corresponding algebraic ...
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Two kinds of algebraic multigrid (AMG) algorithms with three-dimensional equal algebraic structures are constructed on the basis of a two-dimensional coarsing technique. The AMG method and the corresponding algebraic multigrid-preconditioned CG method are applied to elliptic boundary value problems with smooth coefficients and anisotropic problems. Numerical results show that the AMG algorithm is efficient and robust.
We study hybrid search schemes for unstructured peer-to-peer networks. We quantify performance in terms of number of hits, network overhead, and response time. Our schemes combine flooding and random walks, look ahead...
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We study hybrid search schemes for unstructured peer-to-peer networks. We quantify performance in terms of number of hits, network overhead, and response time. Our schemes combine flooding and random walks, look ahead and replication. We consider both regular topologies and topologies with supernodes. We introduce a general search scheme, of which flooding and random walks are special instances, and show how to use locally maintained network information to improve the performance of searching. Our main findings are: (a) a small number of supernodes in an otherwise regular topology can offer sharp savings in the performance of search, both in the case of search by flooding and search by random walk, particularly when it is combined with 1-step replication. We quantify, analytically and experimentally, that the reason of these savings is that the search is biased towards nodes that yield more information. (b) There is a generalization of search, of which flooding and random walk are special instances, which may take further advantage of locally maintained network information, and yield better performance than both flooding and random walk in clustered topologies. The method determines edge critically and is reminiscent of fundamental heuristics from the area of approximation algorithms.
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