Work

Low-Complexity Algorithms for Multichannel Spectral Super-Resolution

Year: 2025

Type: conference-paper

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.

Source: IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)

DOI: 10.1109/icasspw65056.2025.11011075

Authors: Xunmeng Wu, Zai Yang, Zongben Xu

Institution: Xi'an Jiaotong University

Language: English

Topic: Sparse and Compressive Sensing Techniques

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funder: National Natural Science Foundation of China

OpenAlex ID: W4410771608

FWCI: 0.984

Cites: 30

Cited by: 1

Related to: 10