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研究了从声散射场的远场分布的信息来再现声阻抗障碍物形状的反问题,建立了求解这类反问题的一种非线性最优化模型,并提出了数值实现该非线性最优化模型的一种两步调整迭代算法.两步过程的应用使在确定未知障碍物形状的非线性最优化步中未知函数的个数达到了最少,而在调整迭代过程中,通过利用前一迭代步所得重构信息,使重构精度得到了相当大的改进.所建立的反演算法的一个特别吸引人的性质是,只需要远场分布的一个Fourier系数即可对未知声阻抗障碍物作几何物形的设别.对大量具有各种几何形状的二维障碍物的数值算例保证了本算法是实用和有效的. 相似文献
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为研究红外无损探测稳态多热源反演逆问题, 建立不同形状的均质与非均质稳态热传导模型, 其中内热源个数、位置、强度、面积均为未知项. 基于数值算法中有限元算法对模型进行离散分析, 化简有限元矩阵方程, 最终转化为对Ax = b高度欠定方程的求解. 首次利用分段多项式谱截断奇异值分解法处理内热源逆问题, 并对算法进行改进, 有效改善了该算法在处理多热源反演时存在的严重的热源叠加效应. 根据反演出的内热源信息, 利用有限元算法计算重构出整个模型内所有节点的温度分布. 运用数值仿真Comsol软件和具体实物实验对算法进行有效性评估, 并验证算法在不同热传导模型中的表现. 结果表明, 算法能够准确反演出多热源各参量信息, 在非均质材料模型中仍能准确地反演出热源项, 并有效重构出模型内温度场. 该算法可应用于材料无损检测及人体红外医学成像等领域. 相似文献
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首先介绍了迭代正则化方法的理论基础,建立了含有空间电荷密度分布的Fredholm第一类积分方程的反卷积算法,利用数值实验研究了加性高斯白噪声对迭代反卷积算法的影响,以及迭代停止标准对非适定问题的数值解的影响,最后使用该方法求解电介质样品中的空间电荷分布.结果表明,在无噪或者低噪环境下,反卷积算法能够非常好地计算出非适定问题的解.当噪声影响增大,信噪比降低时,反卷积的计算结果受到明显的影响.迭代停止标准对数值解的计算精度起着明显的作用.对实际测量数据进行处理表明,迭代正则化反卷积算法能够计算出固体电介质中的空间电荷分布. 相似文献
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为了准确利用远场得到近场相位分布,提出了多帧相位反演算法.这是一种利用多个远场以实现传统Gerchberg-Saxton(G-S)算法的相位反演方法,其中的新远场是通过叠加已知像差到待测像差后产生的.在此算法的基础上,提出以变形镜面形来实现反演的方法,并通过数值仿真和实验验证了这种基于变形镜面形的多帧G-S相位反演方法的可行性.仿真结果同时还表明,采用4个变形镜面形产生相应的远场,平均仪需50次的迭代便可反演出不同D/r0数值的大气像差,这些反演的像差与其对应待测像差之间的差别的均方根值平均小于0.005 λ. 相似文献
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针对基于主成分分析(PCA)的三维(3D)人脸形状重构不精确的缺点,对位移向量、缩放因子、旋转矩阵、重构系数等参数进行了精确的定义和计算,并对重构模型进行了有效的调整。根据CVL Face Database建立了113个3D人脸形状模型,经迭代运算后重构出了由特征点组成的稀疏3D人脸形状模型。利用径向基函数(RBF)得到了密集3D人脸形状模型。试验结果表明,算法可以得到精确的重构模型,对深度旋转的人脸图像和特征点定位误差也有很好的鲁棒性。 相似文献
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研究了从声散射场的远场分布的信息来再现半空间三维目标几何特征信息的反问题,提出了求解这种非线性不适定问题的一种简单快速算法。该方法的一个特别的性质是只需要通过一个不适定的线性方程组求解,即可简单快速地得到半空间中三维目标几何特征信息的一个清晰的像,而且目标的个数和边界条件的类型等几何与物理的先验信息在本算法中都是不需要的。数值算例保证了本算法的有效性。 相似文献
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基于改进布谷鸟算法反演瞬态热传导问题随温度变化的导热系数.采用Kirchhoff变换将非线性热传导问题转换为线性热传导问题,使用边界元法求解瞬态热传导正问题.将导热系数的反演转化为函数表达式中未知参数的反演,使用改进布谷鸟算法求解未知参数.与共轭梯度法相比,改进布谷鸟算法对迭代初值不敏感;与布谷鸟算法相比,改进布谷鸟算法迭代次数大大减少.数值算例表明对改进布谷鸟算法,增加测点数量迭代次数增加;增加鸟巢数量迭代次数减少;减小测量误差计算结果更精确,同时迭代次数更少.数值算例验证了改进布谷鸟算法反演导热系数的准确性和有效性. 相似文献
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针对高光谱图像像元中端元物质非线性混合的特点,借鉴生物群智能现象,提出一种基于双鸟群优化的高光谱图像非线性解混算法。为进一步提高非线性解混算法的精度,通过模拟鸟群中觅食、警惕以及飞行等行为得到非线性问题的最优解。算法通过双鸟群的迭代优化来交替更新目标函数中的最优解以及非线性模型参数,最终得到高光谱图像端元丰度的最佳估计。仿真实验和光谱数据实验结果表明:双鸟群优化算法迭代收敛,能克服局部最小值问题;相比于同类算法,该算法解混结果的丰度重建误差、平均光谱角距离和像元重建误差3项指标均较小,该算法解混精度高,像元重构效果好,能有效提高高光谱图像非线性解混的精度。 相似文献
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A novel two-step reconstruction scheme using a combined near-infrared and ultrasound technique and its utility in imaging distributions of optical absorption and hemoglobin concentration of breast lesions are demonstrated. In the first-step image reconstruction, the entire tissue volume is segmented based on initial coregistered ultrasound measurements into lesion and background regions. Reconstruction is performed by use of a finer grid for lesion region and a coarse grid for the background tissue. As a result, the total number of voxels with unknown absorption can be maintained on the same order of total measurements, and the matrix with unknown total absorption distribution is appropriately scaled for inversion. In the second step, image reconstruction is refined by optimization of lesion parameters measured from ultrasound images. It is shown that detailed distributions of wavelength-dependent absorption and hemoglobin concentration of breast carcinoma can be obtained with the new reconstruction scheme. 相似文献
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《Waves in Random and Complex Media》2013,23(3):485-500
The application of two techniques for the of shape reconstruction of a perfectly two-dimensional conducting cylinder from mimic measurement data is studied in the present paper. After an integral formulation, the microwave imaging is recast as a nonlinear optimization problem; a cost function is defined by the norm of a difference between the measured scattered electric fields and the calculated scattered fields for an estimated shape of a conductor. Thus, the shape of conductor can be obtained by minimizing the cost function. In order to solve this inverse scattering problem, transverse electric (TE) waves are incident upon the objects and two techniques are employed to solve these problems. The first is based on an asynchronous particle swarm optimization (APSO) and the second is a dynamic differential evolution (DDE). Both techniques have been tested in the case of simulated mimic measurement data contaminated by additive white Gaussian noise. Numerical results indicate that the DDE algorithm and the APSO have almost the same reconstructed accuracy. 相似文献
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Modern thermal power plants are complex technological systems. Therefore, making informed decisions when studying them requires the use of mathematical modeling and nonlinear optimization methods for plant parameter. The most complex task is to solve a mixed optimization problem wherein a part of optimization parameters vary continuously, and the other can take only discrete (integer) values. An effective method is developed to solve a thermal power plant optimization problem with continuous and discrete parameters. The method suggests an iterative procedure for solving continuous nonlinear programming problems and discrete-continuous linear programming problems. For each iteration, we add new constraints obtained by linearizing nonlinear inequality constraints and the objective function of the initial problem to the system of inequality constraints of linear problem. The effectiveness of the proposed method is exemplified by the optimization of a combined cycle power plant with a mixture of working media (the STIG scheme). Design characteristics of heating surface of a waste heat recovery boiler represent the discrete parameters to be optimized. The research demonstrates a considerable reduction in computational effort compared to the branch and bound method. 相似文献
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Compton scattering imaging is a novel radiation imaging method using scattered photons.Its main characteristics are detectors that do not have to be on the opposite side of the source,so avoiding the rotation process.The reconstruction problem of Compton scattering imaging is the inverse problem to solve electron densities from nonlinear equations,which is ill-posed.This means the solution exhibits instability and sensitivity to noise or erroneous measurements.Using the theory for reconstruction of sparse images,a reconstruction algorithm based on total variation minimization is proposed.The reconstruction problem is described as an optimization problem with nonlinear data-consistency constraint.The simulated results show that the proposed algorithm could reduce reconstruction error and improve image quality,especially when there are not enough measurements. 相似文献
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Inspired by the first-order method of Malitsky and Pock, we propose a new variational framework for compressed MR image reconstruction which introduces the application of a rotation-invariant discretization of total variation functional into MR imaging while exploiting BM3D frame as a sparsifying transform. In the first step, we provide theoretical and numerical analysis establishing the exceptional rotation-invariance property of this total variation functional and observe its superiority over other well-known variational regularization terms in both upright and rotated imaging setups. Thereupon, the proposed MRI reconstruction model is presented as a constrained optimization problem, however, we do not use conventional ADMM-type algorithms designed for constrained problems to obtain a solution, but rather we tailor the linesearch-equipped method of Malitsky and Pock to our model, which was originally proposed for unconstrained problems. As attested by numerical experiments, this framework significantly outperforms various state-of-the-art algorithms from variational methods to adaptive and learning approaches and in particular, it eliminates the stagnating behavior of a previous work on BM3D-MRI which compromised the solution beyond a certain iteration. 相似文献
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Patrick Jenny Hamdi A. Tchelepi Seong H. Lee 《Journal of computational physics》2009,228(20):7497-7512
This paper addresses the convergence properties of implicit numerical solution algorithms for nonlinear hyperbolic transport problems. It is shown that the Newton–Raphson (NR) method converges for any time step size, if the flux function is convex, concave, or linear, which is, in general, the case for CFD problems. In some problems, e.g., multiphase flow in porous media, the nonlinear flux function is S-shaped (not uniformly convex or concave); as a result, a standard NR iteration can diverge for large time steps, even if an implicit discretization scheme is used to solve the nonlinear system of equations. In practice, when such convergence difficulties are encountered, the current time step is cut, previous iterations are discarded, a smaller time step size is tried, and the NR process is repeated. The criteria for time step cutting and selection are usually based on heuristics that limit the allowable change in the solution over a time step and/or NR iteration. Here, we propose a simple modification to the NR iteration scheme for conservation laws with S-shaped flux functions that converges for any time step size. The new scheme allows one to choose the time step size based on accuracy consideration only without worrying about the convergence behavior of the nonlinear solver. The proposed method can be implemented in an existing simulator, e.g., for CO2 sequestration or reservoir flow modeling, quite easily. The numerical analysis is confirmed with simulation studies using various test cases of nonlinear multiphase transport in porous media. The analysis and numerical experiments demonstrate that the modified scheme allows for the use of arbitrarily large time steps for this class of problems. 相似文献