2.7k citations · 7.9k across the 98 of their papers we have counts for
6 papers · 2 filters
A Generalization of the Convolution Theorem and its Connections to Non-Stationarity and the Graph Frequency Domain
Alberto Natali, Geert Leus
In this paper, we present a novel convolution theorem which encompasses the well known convolution theorem in (graph) signal processing as well as the one related to time-varying f…
Learning graphs and simplicial complexes from data
Andrei Buciulea, Elvin Isufi, Geert Leus +1
Graphs are widely used to represent complex information and signal domains with irregular support. Typically, the underlying graph topology is unknown and must be estimated from th…
Sensor Selection using the Two-Target Cramér-Rao Bound for Angle of Arrival Estimation
Costas A. Kokke, Mario Coutiño, Laura Anitori +2
Sensor selection is a useful method to help reduce data throughput, as well as computational, power, and hardware requirements, while still maintaining acceptable performance. Alth…
Deep-Learning-Aided Alternating Least Squares for Tensor CP Decomposition and Its Application to Massive MIMO Channel Estimation
Xiao Gong, Wei Chen, Bo Ai +1
CANDECOMP/PARAFAC (CP) decomposition is the mostly used model to formulate the received tensor signal in a massive MIMO system, as the receiver generally sums the components from d…
Graph Signal Processing: History, Development, Impact, and Outlook
Geert Leus, Antonio G. Marques, José M. F. Moura +2
Graph signal processing (GSP) generalizes signal processing (SP) tasks to signals living on non-Euclidean domains whose structure can be captured by a weighted graph. Graphs are ve…
Super-Resolution Harmonic Retrieval of Non-Circular Signals
Yu Zhang, Yue Wang, Zhi Tian +2
This paper proposes a super-resolution harmonic retrieval method for uncorrelated strictly non-circular signals, whose covariance and pseudo-covariance present Toeplitz and Hankel…