标题： 正接近碰撞点源的超分辨 显示英文标题

标题： Super-resolution of positive near-colliding point sources

摘要： In this paper, we analyze the capacity of super-resolution of one-dimensional positive sources. In particular, we consider the same setting as in [arXiv:1904.09186v2 [math.NA]] and generalize the results there to the case of super-resolving positive sources. To be more specific, we consider resolving $d$ positive point sources with $p \leqslant d$ nodes closely spaced and forming a cluster, while the rest of the nodes are well separated. 类似于 [arXiv:1904.09186v2 [math.NA]] 的结果，我们的研究表明，当噪声水平为 $\epsilon \lesssim \mathrm{SRF}^{-2 p+1}$ 时，其中 $\mathrm{SRF}=(\Omega \Delta)^{-1}$，以 $\Omega$ 作为截止频率，$\Delta$ 为节点之间的最小间距，重构聚类节点的 minimax 误差率为 $\frac{1}{\Omega} \mathrm{SRF}^{2 p-2} \epsilon$ 阶，而恢复相应振幅 $\left\{a_j\right\}$ 的误差率则为 $\mathrm{SRF}^{2 p-1} \epsilon$ 阶。 对于非聚类节点，对应于节点和振幅恢复的极小极大速率分别为 $\frac{\epsilon}{\Omega}$ 和 $\epsilon$。 我们的数值实验表明，当分辨正源时，Matrix Pencil 方法达到了上述最优界限。 显示英文摘要

摘要： In this paper, we analyze the capacity of super-resolution of one-dimensional positive sources. In particular, we consider the same setting as in [arXiv:1904.09186v2 [math.NA]] and generalize the results there to the case of super-resolving positive sources. To be more specific, we consider resolving $d$ positive point sources with $p \leqslant d$ nodes closely spaced and forming a cluster, while the rest of the nodes are well separated. Similarly to [arXiv:1904.09186v2 [math.NA]], our results show that when the noise level $\epsilon \lesssim \mathrm{SRF}^{-2 p+1}$, where $\mathrm{SRF}=(\Omega \Delta)^{-1}$ with $\Omega$ being the cutoff frequency and $\Delta$ the minimal separation between the nodes, the minimax error rate for reconstructing the cluster nodes is of order $\frac{1}{\Omega} \mathrm{SRF}^{2 p-2} \epsilon$, while for recovering the corresponding amplitudes $\left\{a_j\right\}$ the rate is of order $\mathrm{SRF}^{2 p-1} \epsilon$. For the non-cluster nodes, the corresponding minimax rates for the recovery of nodes and amplitudes are of order $\frac{\epsilon}{\Omega}$ and $\epsilon$, respectively. Our numerical experiments show that the Matrix Pencil method achieves the above optimal bounds when resolving the positive sources.