From the 1 of 4 linked papers with an AI index.
4 papers
Optimal structured approximation of Fourier subspaces, Toeplitz matrices, and exponential sums
Albert Fannjiang, Weilin Li
The paper shows that the Gradient-MUSIC algorithm can efficiently and minimax‑optimally recover structured objects such as Fourier subspaces, low‑rank Toeplitz/Hankel matrices, and…
Optimality of Gradient-MUSIC for spectral estimation
Albert Fannjiang, Weilin Li, Wenjing Liao
We introduce the Gradient-MUSIC algorithm for estimating the unknown frequencies and amplitudes of a nonharmonic signal from noisy time samples. While the classical MUSIC algorithm…
Multidimensional Gradient-MUSIC: A Global Nonconvex Optimization Framework for Optimal Resolution
Albert Fannjiang, Weilin Li
We develop a multidimensional version of Gradient-MUSIC for estimating the frequencies of a nonharmonic signal from noisy samples. The guiding principle is that frequency recovery…
Noise-Robust One-Bit Diffraction Tomography and Optimal Dose Fractionation
Pengwen Chen, Albert Fannjiang
This study presents a noise-robust framework for 1-bit diffraction tomography, a novel imaging approach that relies on intensity-only binary measurements obtained through coded ape…