Blind source separation (BSS) is a signal processing subject that has recently been
extended to graph signals. Graph signals that are smooth on their own graphs provide an …

Graph matching over two given graphs is a well-established method for re-identifying
obscured node labels within an anonymous graph by matching the corresponding nodes in …

Using smoothness criteria to separate smooth graph signals from their summation is an
approach that has recently been proposed (Mohammadi et al., 2023) and shown to have a …

Separating source signals from observed signals poses significant challenges, particularly
in underdetermined scenarios. Analyzing the sparse relationships among Time-Frequency …

Source separation in an underdetermined reverberation environment is a very challenging
issue. The classical method is based on the expectation–maximization algorithm. However …

In nowadays information era, the types of communication or radar electronic equipment for
both military and civilian applications are increasing significantly, which leads to various …

This paper proposes a method for properly sampling graph signals under smoothness
priors. Unlike many existing approaches that assume bandlimited graph signals, our method …

Performing blind signal separation (BSS) from the domain in which source signals have
difference characteristics is an efficient method to recover sources from the recorded mixture …

The goal of the blind signal separation (BSS) algorithm is to extract each original signal from
observed mixing signals gathered by receiving antennas or sensors. Objective functions and …

Blind source separation under an underdetermined reverberation environment is a very
challenging issue. The classical method is based on the expectation maximization …