In this paper we analyze nonconforming finite element methods for solving a fourth order boundary value problem describing the deformation of a clamped elastic thin plate unilaterally constrained by an elastic obstacl...
In this paper hierarchical cluster and the competitive learning cluster are compared by using molecular data of large size sets. We construct a reproducible matrix to evaluate the quality of clustering, and dead nodes...
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In this paper hierarchical cluster and the competitive learning cluster are compared by using molecular data of large size sets. We construct a reproducible matrix to evaluate the quality of clustering, and dead nodes problem of the competitive learning network is solved by the conscience mechanism. The experimental results show that the hierarchical clustering can represent a multi-level hierarchy which show the tree relation of cluster distance, the competitive learning network has a good clustering reproducible and indicate the effectiveness of clusters for molecular data
The aim of the @neurIST project is to create an IT infrastructure for the management of all processes linked to research, diagnosis and treatment development for complex and multi-factorial diseases. The IT infrastruc...
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We study the regularity properties of solutions for various classes of Volterra functional integrodifferential equations with nonvanishing delays and weakly singular kernels. In particular, we characterize equations i...
The image restoration problems play an important role in remote sensing and astronomical image analysis. One common method for the recovery of a true image from corrupted or blurred image is the least squares error (L...
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The image restoration problems play an important role in remote sensing and astronomical image analysis. One common method for the recovery of a true image from corrupted or blurred image is the least squares error (LSE) method. But the LSE method is unstable in practical applications. A popular way to overcome instability is the Tikhonov regularization. However, difficulties will encounter when adjusting the so-called regularization parameter a. Moreover, how to truncate the iteration at appropriate steps is also challenging. In this paper we use the trust region method to deal with the image restoration problem, meanwhile, the trust region subproblem is solved by the truncated Lanczos method and the preconditioned truncated Lanczos method. We also develop a fast algorithm for evaluating the Kronecker matrix-vector product when the matrix is banded. The trust region method is very stable and robust, and it has the nice property of updating the trust region automatically. This releases us from tedious finding the regularization parameters and truncation levels. Some numerical tests on remotely sensed images are given to show that the trust region method is promising.
Adaptive methods have been rapidly developed and applied in many fields of scientific and engi- neering computing. Reliable and efficient a posteriori error estimates play key roles for both adaptive finite element ...
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Adaptive methods have been rapidly developed and applied in many fields of scientific and engi- neering computing. Reliable and efficient a posteriori error estimates play key roles for both adaptive finite element and boundary element methods. The aim of this paper is to develop a posteriori error estimates for boundary element methods. The standard a posteriori error estimates for boundary element methods are obtained from the classical boundary integral equations. This paper presents hyper-singular a posteriori er- ror estimates based on the hyper-singular integral equations. Three kinds of residuals are used as the esti- mates for boundary element errors. The theoretical analysis and numerical examples show that the hyper- singular residuals are good a posteriori error indicators in many adaptive boundary element computations.
We present a parallel bisection mesh refinement algorithm based on ALBERT (Adaptive multi-Level finite element toolbox using Bisection refinement and Error control by Residual Techniques). The goal is to develop a par...
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We present a parallel bisection mesh refinement algorithm based on ALBERT (Adaptive multi-Level finite element toolbox using Bisection refinement and Error control by Residual Techniques). The goal is to develop a parallel adaptive finite element code suitable for distributed memory parallel computers or PC clusters. An overview on the basic strategy for the parallelization of ALBERT is given. Issues on the parallel mesh refinement are addressed. A modified mesh refinement algorithm, which can be implemented efficiently on distributed memory parallel computers, is proposed and its properties are discussed. Numerical experiments with parallel bisection mesh refinement algorithm are shown.
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