Low-Complexity Algorithms for Multichannel Spectral Super-Resolution
Optimization and Control
2024-11-19 v1
Abstract
This paper studies the problem of multichannel spectral super-resolution with either constant amplitude (CA) or not. We propose two optimization problems based on low-rank Hankel-Toeplitz matrix factorization. The two problems effectively leverage the multichannel and CA structures, while also enabling the design of low-complexity gradient descent algorithms for their solutions. Extensive simulations show the superior performance of the proposed algorithms.
Cite
@article{arxiv.2411.10938,
title = {Low-Complexity Algorithms for Multichannel Spectral Super-Resolution},
author = {Xunmeng Wu and Zai Yang and Zongben Xu},
journal= {arXiv preprint arXiv:2411.10938},
year = {2024}
}