In this work, we propose the construction of two-channel wavelet filter banks for analyzing
functions defined on the vertices of any arbitrary finite weighted undirected graph. These …

In this paper, we propose a novel algorithm to interpolate data defined on graphs, using
signal processing concepts. The interpolation of missing values from known samples …

In this paper, we extend the Nyquist-Shannon theory of sampling to signals defined on
arbitrary graphs. Using spectral graph theory, we establish a cut-off frequency for all …

Modern data analytics applications on graphs often operate on domains where graph
topology is not known a priori, and hence its determination becomes part of the problem …

This paper extends previous results on wavelet filterbanks for data defined on graphs from
the case of orthogonal transforms to more general and flexible biorthogonal transforms. As …

Multiscale transforms designed to process analog and discrete-time signals and images
cannot be directly applied to analyze high-dimensional data residing on the vertices of a …

Graph signal processing deals with signals whose domain, defined by a graph, is irregular.
An overview of basic graph forms and definitions is presented first. Spectral analysis of …

Signal processing on graphs finds applications in many areas. In recent years, renewed
interest on this topic was kindled by two groups of researchers. Narang and Ortega …

Sampling methods for graph signals in the graph spectral domain are presented. Though
the conventional sampling of graph signals can be regarded as sampling in the graph vertex …

We consider the problem of sampling from data defined on the nodes of a weighted graph,
where the edge weights capture the data correlation structure. As shown recently, using …