两个三阶最优化力梯度辛积分器的对称组合

利用已存在的三阶最优化力梯度辛格式以对称组合方法获得两个新的四阶力梯度辛积分器.它们在求解摄动Kepler混沌问题的能量精度和一维定态Schrö,dinger方程的能量本征值精度方面比Forest-Ruth四阶非力梯度辛积分器要好得多,甚至还要明显优越于已有的四阶最优化力梯度辛积分器.     

三维问题边界元法中几乎奇异积分的正则化算法

当源点靠近边界单元时,边界积分方程通常存在几乎奇异积分的计算难题.基于三角形单元,将源点到单元的距离与单元特征长度比值定义为接近度,用于度量边界单元中积分奇异性的程度.将单元上的面积分在局部的极坐标系ρθ下表示,利用一些初等函数的积分公式,获得对变量ρ作单层积分的解析表达式.几乎强奇异和超奇异面积分被转化为沿单元围道上一系列线积分,而Gauss数值积分能够有效计算这些线积分.应用该算法分析三维弹性薄壁结构获得了成功.     

Low‐rank approximation of tensors via sparse optimization

The goal of this paper is to find a low‐rank approximation for a given nth tensor. Specifically, we give a computable strategy on calculating the rank of a given tensor, based on approximating the solution to an NP‐hard problem. In this paper, we formulate a sparse optimization problem via an l₁‐regularization to find a low‐rank approximation of tensors. To solve this sparse optimization problem, we propose a rescaling algorithm of the proximal alternating minimization and study the theoretical convergence of this algorithm. Furthermore, we discuss the probabilistic consistency of the sparsity result and suggest a way to choose the regularization parameter for practical computation. In the simulation experiments, the performance of our algorithm supports that our method provides an efficient estimate on the number of rank‐one tensor components in a given tensor. Moreover, this algorithm is also applied to surveillance videos for low‐rank approximation.     

基于Tikhonov正则参量后验选择策略的PCS颗粒粒度反演方法

采用基于Morozov偏差原理的后验策略来选择最优正则参量,并采用此方法对单峰和多峰分布颗粒系的模拟电场自相关函数进行了反演,结果表明,对于单峰颗粒体系,当电场自相关函数的扰动误差小于0.05时,反演得到的峰值准确,当电场自相关函数的扰动误差大于0.05时,反演得到的峰值偏离所模拟的颗粒粒径.正则参量初始值在0.000 02～2范围内,在反演所得的峰值准确的基础上,正则参量初始值越小,反演得到的分布宽度越窄.收敛误差在0.000 05～50范围内,在保持反演结果稳定的基础上,收敛误差取值越大,反演得到的分布宽度越窄.对于多峰颗粒体系,当颗粒系中的颗粒粒径差别较小时,峰值向平均值偏移,当颗粒系中的颗粒粒径差别较大时,小颗粒粒径分布以噪音的形式出现.     

Regularization extragradient method for Lipschitz continuous mappings and inverse strongly-monotone mappings in Hilbert spaces

The purpose of this paper is to present a regularization variant of the extragradient method for finding a common element of the solution sets for a variational inequality problem involving a -Lipschitz continuous monotone mapping A and for a finite family of λ _i -inverse strongly-monotone operators {A _i } _{i = 1} ^N from a closed convex subset K into the Hilbert space H. This article was submitted by the author in English.     

Nonlocal regularization based on DT-CWT for WMSN video image iterative reconstruction

The prior knowledge of signal is the previous condition of image compressed sensing reconstruction. In order to improve the quality of the priors except for image sparsity, this paper proposes a new model of video image reconstruction. The texture is the important visual feature of video image as a result of its repeat, leading to image global geometrical structures. The nonlocal idea comes from image self-familiar and can represent image detail features from the geometrical point of view. Therefore, the texture geometrical feature of video image is researched, and we take advantage of dual-tree complex wavelet transform to portray the sparsity representation regularization of the texture. What is more, global constrained regularization is constructed with the help of the nonlocal idea. On the basis of the two regularizations above, a new reconstruction model of video image compressed sensing is proposed, which not only preserves the sparsity prior knowledge of image but also improves the quality of prior knowledge of image by promoting geometrical structure. Iterative shrinkage thresholding algorithm is adopted to solve the model leading to a both simple and quick iterative algorithm. Numerical experiments show that our method is efficient for video image recovery, especially preserving the global details of the original video image.     

无穷维Hamilton算子的辛自伴性

本文运用算子扰动理论研究了无穷维Hamilton算子的共轭算子,进而得到了无穷维Hamilton算子为辛自伴算子的若干充分条件.     

Numerical differentiation by radial basis functions approximation

Based on radial basis functions approximation, we develop in this paper a new com-putational algorithm for numerical differentiation. Under an a priori and an a posteriori choice rules for the regularization parameter, we also give a proof on the convergence error estimate in reconstructing the unknown partial derivatives from scattered noisy data in multi-dimension. Numerical examples verify that the proposed regularization strategy with the a posteriori choice rule is effective and stable to solve the numerical differential problem. *The work described in this paper was partially supported by a grant from CityU (Project No. 7001646) and partially supported by the National Natural Science Foundation of China (No. 10571079).     

三维复杂温度场高精度声学测量方法

声学温度场检测技术通过多路径声波传播时间数据,反演被测区域的温度分布。提供了一种高精度的三维复杂温度场的声学测量方法。首先从射线声学角度给出了三维非均匀温度场中声波传播路径的数学模型。在此基础上,将三维温度场的重建问题转化为声波传播路径的求解和温度场的反演问题,建立了基于多项式修正径向基函数(RBF-PR)和改进的Tikhonov正则化三维温度场重建算法。采用两种典型的炉膛三维温度场模型,在信噪比SNR=35 dB下进行了数值模拟,分析了声波传播路径在非均匀温度场中的弯曲特性、算法的重建质量和抗噪性,同时进行了实际炉膛内二维温度场的重建。结果表明了提出的考虑声线弯曲的温度场重建算法具有精度高,抗噪性强、适用性好的特点,为实现高精度的复杂温度场的声学测量提供了有效方法。