Searched for: author%3A%22Leus%2C+G.J.T.%22
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Doğan, D. (author), Leus, G.J.T. (author)
We consider the problem of recovering complex-valued block sparse signals with unknown borders. Such signals arise naturally in numerous applications. Several algorithms have been developed to solve the problem of unknown block partitions. In pattern-coupled sparse Bayesian learning (PCSBL), each coefficient involves its own hyperparameter...
journal article 2024
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Mohammadkarimi, M. (author), Leus, G.J.T. (author), Rajan, R.T. (author)
A new method for joint ranging and Phase Offset (PO) estimation of multiple drones/aircrafts is proposed in this paper. The proposed method employs the superimposed uncoordinated Automatic Dependent Surveillance-Broadcast (ADS-B) packets broadcasted by drones/aircrafts for joint range and PO estimation. It jointly estimates range and PO prior...
journal article 2024
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Brown, Michael D. (author), Generowicz, Bastian S. (author), Dijkhuizen, Stephanie (author), Koekkoek, Sebastiaan K.E. (author), Strydis, C. (author), Bosch, Johannes G. (author), Arvanitis, Petros (author), Springeling, Geert (author), Leus, G.J.T. (author), De Zeeuw, Chris I. (author), Kruizinga, P. (author)
Four-dimensional ultrasound imaging of complex biological systems such as the brain is technically challenging because of the spatiotemporal sampling requirements. We present computational ultrasound imaging (cUSi), an imaging method that uses complex ultrasound fields that can be generated with simple hardware and a physical wave prediction...
journal article 2024
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Mohammadkarimi, M. (author), Leus, G.J.T. (author), Rajan, R.T. (author)
In this paper, we propose a new method for joint ranging and Phase Offset (PO) estimation of multiple transponder-equipped aviation vehicles (TEAVs), including Manned Aerial Vehicles (MAVs) and Unmanned Aerial Vehicles (UAVs). The proposed method employs the overlapping uncoordinated Automatic Dependent Surveillance-Broadcast (ADS-B) packets...
conference paper 2024
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Ramamohan, Krishnaprasad Nambur (author), Chepuri, Sundeep Prabhakar (author), Comesana, Daniel Fernandez (author), Leus, G.J.T. (author)
In this work, we consider the self-calibration problem of joint calibration and direction-of-Arrival (DOA) estimation using acoustic sensor arrays. Unlike many previous iterative approaches, we propose solvers that can be readily used for both linear and non-linear arrays for jointly estimating the sensor gain, phase errors, and the source...
journal article 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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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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Leus, G.J.T. (author), Marques, Antonio G. (author), Moura, Jose M.F. (author), Ortega, Antonio (author), Shuman, David I. (author)
Signal processing (SP) excels at analyzing, processing, and inferring information defined over regular (first continuous, later discrete) domains such as time or space. Indeed, the last 75 years have shown how SP has made an impact in areas such as communications, acoustics, sensing, image processing, and control, to name a few. With the...
journal article 2023
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Liu, Lingya (author), Hua, Cunqing (author), Xu, Jing (author), Leus, G.J.T. (author), Wang, Yiyin (author)
This article focuses on greedy approaches to select the most informative k sensors from N candidates to maximize the Fisher information, i.e., the determinant of the Fisher information matrix (FIM), which indicates the volume of the information ellipsoid (VIE) constructed by the FIM. However, it is a critical issue for conventional greedy...
journal article 2023
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Yang, Qiuling (author), Coutino, Mario (author), Leus, G.J.T. (author), Giannakis, Georgios B. (author)
Graph-based learning and estimation are fundamental problems in various applications involving power, social, and brain networks, to name a few. While learning pair-wise interactions in network data is a well-studied problem, discovering higher-order interactions among subsets of nodes is still not yet fully explored. To this end, encompassing...
journal article 2023
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van der Werf, I. (author), Dol, H. S. (author), Blom, K. (author), Heusdens, R. (author), Hendriks, R.C. (author), Leus, G.J.T. (author)
In this paper, we show the mathematical equivalence of two popular modulation schemes: OSDM and OTFS. The former is mainly used in underwater acoustic communications, while the latter scheme is a promising modulation technique in radio-frequency communications. Although literature suggests a link between the two modulation schemes by connecting...
journal article 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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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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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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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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Liu, Chengen (author), Leus, G.J.T. (author), Isufi, E. (author)
The edge flow reconstruction task consists of retreiving edge flow signals from corrupted or incomplete measurements. This is typically solved by a regularized optimization problem on higher-order networks such as simplicial complexes and the corresponding regularizers are chosen based on prior knowledge. Tailoring this prior to the setting...
journal article 2023
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van der Meulen, P.Q. (author), Coutino, Mario (author), Bosch, Johannes G. (author), Kruizinga, P. (author), Leus, G.J.T. (author)
We consider the scenario of finding the transfer function of an aberrating layer in front of a receiving ultrasound (US) array, assuming a separate non-aberrated transmit source. We propose a method for blindly estimating this transfer function without exact knowledge of the ultrasound sources or acoustic contrast image, and without directly...
journal article 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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