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Machine learning has been successfully applied to various fields in computational science and engineering. In this paper, we propose interfaced neural networks (INNs) to solve interface problems with ...
Machine learning has been successfully applied to various fields in computational science and engineering. In this paper, we propose interfaced neural networks (INNs) to solve interface problems with ...
Heterogeneous computers with processors and accelerators are becoming widespread in scientific computing. However,it is difficult to program hybrid architectures and there is no commonly accepted prog...
In this paper, a standard PDE for the pricing of arithmetic average strike Asian call option is presented. A Crank-Nicolson Implicit Method and a Higher Order Compact finite difference scheme for this...
针对反差较低且包含噪声污染的灰度图像,设计分段线性拉伸函数,引入TV下降流,建立新的偏微分方程(PDE)数学模型。该模型通过设置参数 灵活控制去噪和反差增强的程度,实现2种灰度图像处理手段的同步进行。对比实验表明,该方法可有效缓解传统处理方法存在的问题,在抑制噪声的同时增强图像的反差。
采用非线性扩散模型建立超分辨率图像重构的偏微分方程,利用各向异性扩散方程的方向选择平滑的特性,在重构高分辨率图像的同时能够很好地消除系统噪声,保持细节信息。实验结果表明,该方法有效地提高了重构的图像质量,在视觉观察和数值评价上都优于原有正则化方法,并且对不同噪声水平的图像具有很好的鲁棒性。
基于PDE的非线性扩散滤波对接近高斯分布的噪声消除可取得好的效果,但对于脉冲噪声其效果并不理想。从Perona&Malik模型的扩散系数函数出发,对其函数性质进行分析。通过改进扩散系数函数中的边缘阈值,使其能在消除高梯度图像噪声的同时更好地保持边缘,在一定程序上克服了边缘保持与噪声消除之间的矛盾。
This work is focused on the solvability of initial-boundary value problems for degenerate parabolic partial differential equations that arise in the pricing of Asian options, and on the investigation...

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