Skip to main navigation Skip to search Skip to main content

Low-Complexity Algorithms for Multichannel Spectral Super-Resolution

  • Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publication2025 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops, ICASSPW 2025 - Workshop Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331519315
DOIs
StatePublished - 2025
Event2025 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops, ICASSPW 2025 - Hyderabad, India
Duration: 6 Apr 202511 Apr 2025

Publication series

Name2025 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops, ICASSPW 2025 - Workshop Proceedings

Conference

Conference2025 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops, ICASSPW 2025
Country/TerritoryIndia
CityHyderabad
Period6/04/2511/04/25

Keywords

  • Hankel-Toeplitz matrix
  • Multiple measurements vectors
  • constant amplitude

Fingerprint

Dive into the research topics of 'Low-Complexity Algorithms for Multichannel Spectral Super-Resolution'. Together they form a unique fingerprint.

Cite this