scholar.google.com › citations
We study the problem of sampling k-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at ...
People also ask
What is the sampling theorem for bandlimited signals?
What is the spectrum of a bandlimited signal?
What is the bandlimited frequency?
Nov 16, 2015 · We propose two sampling strategies that consist in selecting a small subset of nodes at random. The first strategy is non-adaptive, i.e., ...
Abstract. The signal processing on graphs has been widely used in var- ious fields, including machine learning, classification and network signal.
Feb 16, 2024 · In this paper, we are interested in how to sample based on sign information in an online manner, by which the direction of the original graph ...
Based on the relationship between the interpolation and sampling operators, a sampling theorem for bandlimited graph signals is proposed, and its physical ...
Abstract. The signal processing on graphs has been widely used in var- ious fields, including machine learning, classification and network signal.
Jan 21, 2018 · In this paper, we discuss the sampling of bandlimited graph signals based on the theory of function spaces, which is consistent with the pattern ...
A critical challenge in graph signal processing is the sampling of bandlimited graph signals; signals that are sparse in a well-defined graph Fourier domain.
Abstract—In this paper we propose a novel vertex based sampling method for k-bandlimited signals lying on arbitrary graphs, that has a reasonable ...
When finite-dimensional vectors represent graph signals, we can use the proposed sampling theory to perfectly recover those graph signals that are bandlimited, ...