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Natali, A. (author), Coutino, Mario (author), Isufi, E. (author), Leus, G.J.T. (author)Signal processing and machine learning algorithms for data sup-ported over graphs, require the knowledge of the graph topology. Unless this information is given by the physics of the problem (e.g., water supply networks, power grids), the topology has to be learned from data. Topology identification is a challenging task, as the problem is often...conference paper 2021
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Leus, G.J.T. (author), Yang, Maosheng (author), Coutino, Mario (author), Isufi, E. (author)To deal with high-dimensional data, graph filters have shown their power in both graph signal processing and data science. However, graph filters process signals exploiting only pairwise interactions between the nodes, and they are not able to exploit more complicated topological structures. Graph Volterra models, on the other hand, are also...conference paper 2021
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Coutino, Mario (author), Isufi, E. (author), Maehara, T. (author), Leus, G.J.T. (author)In this work, we explore the state-space formulation of network processes to recover the underlying network structure (local connections). To do so, we employ subspace techniques borrowed from system identification literature and extend them to the network topology inference problem. This approach provides a unified view of the traditional...conference paper 2020
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Li, Qiongxiu (author), Coutino, Mario (author), Leus, G.J.T. (author), Christensen, M. Graesboll (author)With an increasingly interconnected and digitized world, distributed signal processing and graph signal processing have been proposed to process its big amount of data. However, privacy has become one of the biggest challenges holding back the widespread adoption of these tools for processing sensitive data. As a step towards a solution, we...conference paper 2020
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Yang, Qiuling (author), Coutino, Mario (author), Wang, Gang (author), Giannakis, Georgios B. (author), Leus, G.J.T. (author)To perform any meaningful optimization task, distribution grid operators need to know the topology of their grids. Although power grid topology identification and verification has been recently studied, discovering instantaneous interplay among subsets of buses, also known as higher-order interactions in recent literature, has not yet been...conference paper 2020
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Wang, Yue (author), Zhang, Yu (author), Tian, Zhi (author), Leus, G.J.T. (author), Zhang, Gong (author)This paper develops an enhanced low-rank structured covariance reconstruction (LRSCR) method based on the decoupled atomic norm minimization (D-ANM), for super-resolution two-dimensional (2D) harmonic retrieval with multiple measurement vectors. This LRSCR-D-ANM approach exploits a potential structure hidden in the covariance by transferring the...conference paper 2020
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Sharma, S. (author), Hari, K.V.S. (author), Leus, G.J.T. (author)A novel class of k-space trajectories for magnetic resonance imaging (MRI) sampling using space filling curves (SFCs) is presented here. More specifically, Peano, Hilbert and Sierpinski curves are used. We propose 1-shot and 4-shot variable density SFCs by utilizing the space coverage provided by SFCs in different iterations. The proposed...conference paper 2020
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Das, Bishwadeep (author), Isufi, E. (author), Leus, G.J.T. (author)Diffusion-based semi-supervised learning on graphs consists of diffusing labeled information of a few nodes to infer the labels on the remaining ones. The performance of these methods heavily relies on the initial labeled set, which is either generated randomly or using heuristics. The first sometimes leads to unsatisfactory results because...conference paper 2020
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Wang, F. (author), Tian, Zhi (author), Fang, Jun (author), Leus, G.J.T. (author)This paper concerns wideband direction of arrival (DoA) estimation with sparse linear arrays (SLAs). We rely on the assumption that the power spectrum of the wideband sources is the same up to a scaling factor, which could in theory allow us to resolve not only more sources than the number of antennas but also more sources than the number of...conference paper 2020
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Generowicz, B.S. (author), Verhoef, Luuk (author), Mastik, Frits (author), Dijkhuizen, Stefanie (author), van Dorp, Nikki (author), Voorneveld, Jason (author), Bosch, Johannes (author), Kumar, Karishma (author), Leus, G.J.T. (author)Power Doppler (PD) imaging has become a staple in high frame rate ultrasound imaging due to its ability to image small vessels and slow-moving flows, such as in the case of imaging blood flow in the brain. Alternatively, color Doppler (CD) can be used to determine the one-dimensional directional information of the blood scatterers. This can help...conference paper 2020
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Coutino, Mario (author), Karanikolas, Georgios V (author), Leus, G.J.T. (author), Giannakis, Georgios B. (author)Link prediction is one of the core problems in network and data science with widespread applications. While predicting pairwise nodal interactions (links) in network data has been investigated extensively, predicting higher-order interactions (higher-order links) is still not fully understood. Several approaches have been advocated to predict...conference paper 2020
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Sharma, S. (author), Hari, K.V.S. (author), Leus, G.J.T. (author)The development of compressed sensing (CS) techniques for magnetic resonance imaging (MRI) is enabling a speedup of MRI scanning. To increase the incoherence in the sampling, a random selection of points on the k-space is deployed and a continuous trajectory is obtained by solving a traveling salesman problem (TSP) through these points. A...conference paper 2020
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Natali, A. (author), Coutino, Mario (author), Leus, G.J.T. (author)Data defined over a network have been successfully modelled by means of graph filters. However, although in many scenarios the connectivity of the network is known, e.g., smart grids, social networks, etc., the lack of well-defined interaction weights hinders the ability to model the observed networked data using graph filters. Therefore, in...conference paper 2020
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Natali, A. (author), Isufi, E. (author), Leus, G.J.T. (author)The forecasting of multi-variate time processes through graph-based techniques has recently been addressed under the graph signal processing framework. However, problems in the representation and the processing arise when each time series carries a vector of quantities rather than a scalar one. To tackle this issue, we devise a new framework and...conference paper 2020
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Zhang, Yu (author), Wang, Yue (author), Tian, Zhi (author), Leus, G.J.T. (author), Zhang, Gong (author)This paper aims at developing low-complexity solutions for super-resolution two-dimensional (2D) harmonic retrieval via covariance reconstruction. Given the collected sample covariance, a novel gridless compressed sensing approach is designed based on the atomic norm minimization (ANM) technique. The key is to perform a redundancy reduction (RR)...conference paper 2020
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Hagenaars, E. (author), Pandharipande, A. (author), Frimout, E. (author), Leus, G.J.T. (author)We consider the problem of detecting sensor commissioning in the form of determining the sensor layout. We address this problem for single-pixel thermopile sensors, located at the ceiling, that provide remote temperature measurements for people counting applications and HVAC controls. We employ a random forest classifier to determine the...conference paper 2020
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Fernandez-Menduina, S. (author), Krahmer, F. (author), Leus, G.J.T. (author), Bhandari, A. (author)Direction-of-arrival (DoA) estimation is a mature topic with decades of history. Despite the progress in the field, very few papers have looked at the problem of DoA estimation with unknown dynamic range. Consider the case of space exploration or near-field and far-field emitters. In such settings, the amplitude of the impinging wavefront can be...conference paper 2020
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Yang, M. (author), Coutino, Mario (author), Isufi, E. (author), Leus, G.J.T. (author)While regularization on graphs has been successful for signal reconstruction, strategies for controlling the bias-variance trade-off of such methods have not been completely explored. In this work, we put forth a node varying regularizer for graph signal reconstruction and develop a minmax approach to design the vector of regularization...conference paper 2020
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van der Meulen, P.Q. (author), Coutino, Mario (author), Kruizinga, P. (author), Bosch, J.G. (author), Leus, G.J.T. (author)We consider the scenario of finding the transfer function of an aberrating layer in front of an ultrasound array. We are interested in blindly estimating this transfer function without prior knowledge of the unknown ultrasound sources or ultrasound contrast image. The algorithm gives an exact solution if the matrix representing the aberration...conference paper 2020
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Nambur Ramamohan, K. (author), Chepuri, S.P. (author), Comesana, Daniel Fernandez (author), Leus, G.J.T. (author)In this paper, the focus is on the gain and phase calibration of sparse sensor arrays to localize more sources than the number of physical sensors. The proposed technique is a blind calibration method as it does not require any calibrator sources. Joint estimation of the gain errors, phase errors, and source directions is a complicated non...conference paper 2019