首页> 外文会议>IEEE International Conference on Acoustics, Speech and Signal Processing >HIGHER ORDER EXPONENTIAL SPLITTINGS FOR THE FAST NON-LINEAR FOURIER TRANSFORM OF THE KORTEWEG-DE VRIES EQUATION
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HIGHER ORDER EXPONENTIAL SPLITTINGS FOR THE FAST NON-LINEAR FOURIER TRANSFORM OF THE KORTEWEG-DE VRIES EQUATION

机译:Korteweg-de VRIES方程的快速非线性傅立叶变换的高阶指数分配

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Non-linear Fourier Transforms (NFTs) enable the analysis of signals governed by certain non-linear evolution equations in a way that is analogous to how the conventional Fourier transform is used to analyse linear wave equations. Recently, fast numerical algorithms have been derived for the numerical computation of certain NFTs. In this paper, we are primarily concerned with fast NFTs with respect to the Korteweg-de Vries equation (KdV), which describes e.g. the evolution of waves in shallow water. We find that in the KdV case, the fast NFT can be more sensitive to numerical errors caused by an exponential splitting. We present higher order splittings that reduce these errors and are compatible with the fast NFT. Furthermore we demonstrate for the NSE case that using these splittings can make the accuracy of the fast NFT match that of the conventional NFT.
机译:非线性傅立叶变换(NFT)能够以类似于传统傅里叶变换如何分析线性波动方程的方式的方式分析由某些非线性演化方程所控制的信号。最近,已经导出了用于某些NFT的数值计算的快速数值算法。在本文中,我们主要涉及关于Korteweg-de Vries方程(KDV)的快速NFT,其描述了例如e.g。浅水中波浪的演变。我们发现在KDV的情况下,快速NFT可以对由指数分裂引起的数值误差更敏感。我们提出了更高阶的分裂,减少了这些错误,并与快速NFT兼容。此外,我们向NSE案例展示了使用这些分裂器可以使传统NFT的快速NFT匹配的准确性。

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