In this paper, we theoretically propose a new hashing scheme to establish the sparse Fourier transform in high-dimensional space. The estimation of the algorithm complexity shows that this sparse Fourier transform can overcome the curse of dimensionality. To the best of our knowledge, this is the first polynomial-time algorithm to recover the high-dimensional continuous frequencies.

翻译：在本文中,我们理论上提出一个新的散列计划,在高维空间建立稀有的傅里叶变异。算法复杂性的估计表明,这种稀有的傅里叶变异可以克服维度的诅咒。据我们所知,这是第一个恢复高维连续频率的多元时算法。