Blind Deconvolution of Nonstationary Graph Signals over Shift-Invariant Channels
Information Theory
2025-08-26 v1 Signal Processing
math.IT
Abstract
In this paper, we investigate blind deconvolution of nonstationary graph signals from noisy observations, transmitted through an unknown shift-invariant channel. The deconvolution process assumes that the observer has access to the covariance structure of the original graph signals. To evaluate the effectiveness of our channel estimation and blind deconvolution method, we conduct numerical experiments using a temperature dataset in the Brest region of France.
Cite
@article{arxiv.2508.17210,
title = {Blind Deconvolution of Nonstationary Graph Signals over Shift-Invariant Channels},
author = {Ali Zare and Yao Shi and Qiyu Sun},
journal= {arXiv preprint arXiv:2508.17210},
year = {2025}
}