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- Santiago Segarra, Antonio G. Marques, Gonzalo Mateos, Alejandro R. Ribeiro
- IEEE Transactions on Signal and Information…
- 2016

We address the problem of identifying the structure of an undirected graph from the observation of signals defined on its nodes. Fundamentally, the unknown graph encodes direct relationships between… (More)

- Antonio G. Marques, Santiago Segarra, Geert Leus, Alejandro R. Ribeiro
- IEEE Transactions on Signal Processing
- 2016

A new scheme to sample signals defined on the nodes of a graph is proposed. The underlying assumption is that such signals admit a sparse representation in a frequency domain related to the structure… (More)

- Antonio G. Marques, Santiago Segarra, Geert Leus, Alejandro R. Ribeiro
- IEEE Transactions on Signal Processing
- 2017

Stationarity is a cornerstone property that facilitates the analysis and processing of random signals in the time domain. Although time-varying signals are abundant in nature, in many practical… (More)

- Santiago Segarra, Antonio G. Marques, Alejandro R. Ribeiro
- IEEE Transactions on Signal Processing
- 2017

We study the optimal design of graph filters (GFs) to implement arbitrary linear transformations between graph signals. GFs can be represented by matrix polynomials of the graph-shift operator (GSO).… (More)

- Santiago Segarra, Antonio G. Marques, Gonzalo Mateos, Alejandro R. Ribeiro
- IEEE Statistical Signal Processing Workshop (SSP)
- 2016

Network topology inference is a cornerstone problem in statistical analyses of complex systems. In this context, the fresh look advocated here permeates benefits from convex optimization and graph… (More)

We study the design of graph filters to implement arbitrary linear transformations between graph signals. Graph filters can be represented by matrix polynomials of the graph-shift operator, which… (More)

- Santiago Segarra, Gonzalo Mateos, Antonio G. Marques, Alejandro R. Ribeiro
- IEEE Transactions on Signal Processing
- 2017

Network processes are often represented as signals defined on the vertices of a graph. To untangle the latent structure of such signals, one can view them as outputs of linear graph filters modeling… (More)

- Santiago Segarra, Antonio G. Marques, Geert Leus, Alejandro R. Ribeiro
- IEEE Transactions on Signal Processing
- 2016

New schemes to recover signals defined in the nodes of a graph are proposed. Our focus is on reconstructing bandlimited graph signals, which are signals that admit a sparse representation in a… (More)

- Santiago Segarra, Antonio G. Marques, Alejandro R. Ribeiro
- 53rd Annual Allerton Conference on Communication…
- 2015

A signal in a network (graph) can be defined as a vector whose elements represent the value of a given magnitude at the different nodes. A linear network (graph) operator is then a linear… (More)

We address the problem of inferring an undirected graph from nodal observations, which are modeled as non-stationary graph signals generated by local diffusion dynamics that depend on the structure… (More)