This paper studies the problem of parameter estimation for the multifrequency sine signals,
which have multiple characteristic parameters such as the amplitudes, phases, and …

Graph sampling set selection, where a subset of nodes are chosen to collect samples to
reconstruct a smooth graph signal, is a fundamental problem in graph signal processing …

Graph sampling addresses the problem of selecting a node subset in a graph to collect
samples, so that a K-bandlimited signal can be reconstructed with high fidelity. Assuming an …

Graph signal sampling is the problem of selecting a subset of representative graph vertices
whose values can be used to interpolate missing values on the remaining graph vertices …

We propose a generalized sampling framework for stochastic graph signals. Stochastic
graph signals are characterized by graph wide sense stationarity (GWSS) which is an …

For the interpolation of graph signals with generalized shifts of a graph basis function (GBF),
we introduce the concept of positive definite functions on graphs. This concept merges …

Point cloud (PC)—a collection of discrete geometric samples of a 3D object's surface—is
typically large, which entails expensive subsequent operations. Thus, PC sub-sampling is of …

This brief investigates the problem of Graph Signal Recovery (GSR) when the topology of
the graph is not known in advance. In this brief, the elements of the weighted adjacency …

Matrix completion algorithms fill missing entries in a large matrix given a subset of observed
samples. The problem of how to pre-select a subset of entries for sampling to maximize the …

The lifetime of an Internet of Things (IoT) system consisting of battery-powered devices can
be increased by minimizing the number of transmissions per device while not excessively …