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20162023
most citedOnline Change Point Detection for Weighted and Directed Random Dot Product Graphs

8 citations · 16 across the 15 of their papers we have counts for

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Showing 2018 · eess.SPShow all

6 papers · 2 filters

eess.SP2018

Connecting the Dots: Identifying Network Structure via Graph Signal Processing

Gonzalo Mateos, Santiago Segarra, Antonio G. Marques +1

Network topology inference is a prominent problem in Network Science. Most graph signal processing (GSP) efforts to date assume that the underlying network is known, and then analy…

eess.SP2018

A Novel Scheme for Support Identification and Iterative Sampling of Bandlimited Graph Signals

Abolfazl Hashemi, Rasoul Shafipour, Haris Vikalo +1

We study the problem of sampling and reconstruction of bandlimited graph signals where the objective is to select a node subset of prescribed cardinality that ensures interpolation…

eess.SP2018

Towards Accelerated Greedy Sampling and Reconstruction of Bandlimited Graph Signals

Abolfazl Hashemi, Rasoul Shafipour, Haris Vikalo +1

We study the problem of sampling and reconstructing spectrally sparse graph signals where the objective is to select a subset of nodes of prespecified cardinality that ensures inte…

eess.SP2018

A Directed Graph Fourier Transform with Spread Frequency Components

Rasoul Shafipour, Ali Khodabakhsh, Gonzalo Mateos +1

We study the problem of constructing a graph Fourier transform (GFT) for directed graphs (digraphs), which decomposes graph signals into different modes of variation with respect t…

eess.SP2018

Blind Identification of Invertible Graph Filters with Multiple Sparse Inputs

Chang Ye, Rasoul Shafipour, Gonzalo Mateos

This paper deals with problem of blind identification of a graph filter and its sparse input signal, thus broadening the scope of classical blind deconvolution of temporal and spat…

eess.SP2018

Identifying the Topology of Undirected Networks from Diffused Non-stationary Graph Signals

Rasoul Shafipour, Santiago Segarra, Antonio G. Marques +1

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…