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Zhang, Yu (author), Wang, Yue (author), Tian, Zhi (author), Leus, G.J.T. (author), Zhang, Gong (author)This paper proposes a super-resolution harmonic retrieval method for uncorrelated strictly non-circular signals, whose covariance and pseudo-covariance present Toeplitz and Hankel structures, respectively. Accordingly, the augmented covariance matrix constructed by the covariance and pseudo-covariance matrices is not only low rank but also...conference paper 2023
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Natali, A. (author), Leus, G.J.T. (author)Fitting a polynomial to observed data is an ubiquitous task in many signal processing and machine learning tasks, such as interpolation and prediction. In that context, input and output pairs are available and the goal is to find the coefficients of the polynomial. However, in many applications, the input may be partially known or not known at...conference paper 2023
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van der Hoeven, Jelmer (author), Natali, A. (author), Leus, G.J.T. (author)Forecasting time series on graphs is a fundamental problem in graph signal processing. When each entity of the network carries a vector of values for each time stamp instead of a scalar one, existing approaches resort to the use of product graphs to combine this multidimensional information, at the expense of creating a larger graph. In this...conference paper 2023
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Hu, Yuyang (author), Doğan, D. (author), Brown, Michael (author), Bulot, Mahé (author), Ferin, Guillaume (author), Leus, G.J.T. (author), Kruizinga, P. (author), Steen, Antonius F.W. (author), Bosch, Johannes G. (author)It has been previously demonstrated that applying an aberrating mask for 2D compressive imaging using a low number of sensors (elements) can significantly improve image resolution, as evaluated via the point spread function. Here we investigate the potential to apply a similar approach for 3D flow monitoring. We conducted a 3D k-Wave simulation...conference paper 2023
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Kokke, C.A. (author), Coutino, Mario (author), Anitori, Laura (author), Heusdens, R. (author), Leus, G.J.T. (author)Sensor selection is a useful method to help reduce data throughput, as well as computational, power, and hardware requirements, while still maintaining acceptable performance. Although minimizing the Cramér-Rao bound has been adopted previously for sparse sensing, it did not consider multiple targets and unknown source models. In this work, we...conference paper 2023
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Kokke, C.A. (author), Coutiño, Mario (author), Heusdens, R. (author), Leus, G.J.T. (author), Anitori, Laura (author)Integrated sidelobe level is a useful measure to quantify robustness of a waveform-filter pair to unknown range clutter and multiple closely located targets. Sidelobe suppression on receive will incur a loss in the signal to noise ratio after pulse compression. We derive a pulse compression filter that has the greatest integrated sidelobe...conference paper 2023
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Wang, Yujie (author), Zhang, Qunfei (author), Ma, Shengqian (author), Zhang, Lingling (author), Han, Jing (author), Leus, G.J.T. (author)Differential orthogonal signal-division multiplexing (OSDM) is attractive for underwater acoustic (UWA) communications because it can eliminate channel estimation, resulting in a substantial reduction of complexity at the receiver. However, when the channel is time-varying, it may suffer from serious inter-vector interference (IVI), which is...conference paper 2023
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Doğan, D. (author), Leus, G.J.T. (author)We consider the problem of recovering block-sparse signals with unknown boundaries. Such signals arise naturally in various applications. Recent literature introduced a pattern-coupled or clustered Gaussian prior, in which each coefficient involves its own hyperparameter as well as its immediate neighbors' hyperparameters. Some methods use a...conference paper 2023
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Kokke, C.A. (author), Coutino, Mario (author), Heusdens, R. (author), Leus, G.J.T. (author)Sensor selection is a useful method to help reduce computational, hardware, and power requirements while maintaining acceptable performance. Although minimizing the Cramér-Rao bound has been adopted previously for sparse sensing, it did not consider multiple targets and unknown target directions. We propose to tackle the sensor selection problem...conference paper 2023
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Yang, Maosheng (author), Isufi, E. (author), Leus, G.J.T. (author)Graphs can model networked data by representing them as nodes and their pairwise relationships as edges. Recently, signal processing and neural networks have been extended to process and learn from data on graphs, with achievements in tasks like graph signal reconstruction, graph or node classifications, and link prediction. However, these...conference paper 2022
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He, Y. (author), Coutino, Mario (author), Isufi, E. (author), Leus, G.J.T. (author)In this work, we focus on partitioning dynamic graphs with two types of nodes (bi-colored), though not necessarily bipartite graphs. They commonly appear in communication network applications, e.g., one color being base stations, the other users, and the dynamic process being the varying connection status between base stations and moving...conference paper 2022
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Kokke, C.A. (author), Coutino, Mario (author), Heusdens, R. (author), Leus, G.J.T. (author), Anitori, L. (author)Doppler velocity estimation in pulse-Doppler radar is done by evaluating the target returns of bursts of pulses. While this provides convenience and accuracy, it requires multiple pulses. In adaptive and cognitive radar systems, the ability to adapt on consecutive pulses, instead of bursts, brings potential performance benefits. Hence, with...conference paper 2022
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Masoumi, H. (author), Myers, N.J. (author), Leus, G.J.T. (author), Wahls, S. (author), Verhaegen, M.H.G. (author)Fast millimeter wave (mmWave) channel estimation techniques based on compressed sensing (CS) suffer from low signal-to-noise ratio (SNR) in the channel measurements, due to the use of wide beams. To address this problem, we develop an in-sector CS-based mmWave channel estimation technique that focuses energy on a sector in the angle domain....conference paper 2022
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Romero, Daniel (author), Viet, Pham Q. (author), Leus, G.J.T. (author)Mobile base stations on board unmanned aerial vehicles (UAVs) promise to deliver connectivity to those areas where the terrestrial infrastructure is overloaded, damaged, or absent. A fundamental problem in this context involves determining a minimal set of locations in 3D space where such aerial base stations (ABSs) must be deployed to provide...conference paper 2022
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Hu, Yuyang (author), Brown, Michael (author), Doğan, D. (author), Leus, G.J.T. (author), Kruizinga, P. (author), Van Der Steen, Antonius F.W. (author), Bosch, Johannes G. (author)We intend to develop an ultrasound compressive imaging device to perform carotid artery (CA) function and flow monitoring/imaging by using just a few single element transducers equipped with spatial coding masks. The spatially unique impulse responses can be exploited in compressive reconstructions. To explore the potential of different...conference paper 2022
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Sharma, Shubham (author), Hari, K.V.S. (author), Leus, G.J.T. (author)Variable density sampling of the k-space in MRI is an integral part of trajectory design. It has been observed that data-driven trajectory design methods provide a better image reconstruction as compared to trajectories obtained from a fixed or a parametric density function. In this paper, a data-driven strategy has been proposed to obtain non...conference paper 2022
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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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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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Doğan, D. (author), Kruizinga, P. (author), Bosch, Johannes G. (author), Leus, G.J.T. (author)Ultrasound imaging of the vasculature has major significance for the detection of cardiovascular diseases and cancer. However, limited spatial resolution or long acquisition times of existing techniques limit the visualization of the microvascular structures. Enforcing sparsity in the underlying vasculature as well as exploiting statistical...conference paper 2021
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Natali, A. (author), Isufi, E. (author), Coutino, Mario (author), Leus, G.J.T. (author)Topology identification is an important problem across many disciplines, since it reveals pairwise interactions among entities and can be used to interpret graph data. In many scenarios, however, this (unknown) topology is time-varying, rendering the problem even harder. In this paper, we focus on a time-varying version of the structural...conference paper 2021