论文标题
关于傅立叶子膜SVD的计算
On the computation of the SVD of Fourier submatrices
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
Contiguous submatrices of the Fourier matrix are known to be ill-conditioned. In a recent paper in SIAM Review A. Barnett has provided new bounds on the rate of ill-conditioning of the discrete Fourier submatrices. In this paper we focus on the corresponding singular value decomposition. The singular vectors go by the name of periodic discrete prolate spheroidal sequences (P-DPSS). The singular values exhibit an initial plateau, which depends on the dimensions of the submatrix, after which they decay rapidly. The latter regime is known as the plunge region and it is compatible with the submatrices being ill-conditioned. The discrete prolate sequences have received much less study than their continuous counterparts, prolate spheroidal wave functions, associated with continuous Fourier transforms and widely studied following the work of Slepian in the 1970's. In this paper we collect and expand known results on the stable numerical computation of the singular values and vectors of Fourier submatrices. We illustrate the computations and point out a few applications in which Fourier submatrices arise.
