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Harnessing wavefront curvature and spatial correlation in noncoherent MIMO communications
(Institute of Electrical and Electronics Engineers (IEEE), 2025)
Article
Open AccessNoncoherent communication systems have regained interest due to the growing demand for high-mobility and low-latency applications. Most existing studies using large antenna arrays rely on the far-field approximation, which ... -
Robust energy-efficient analog beamforming under short packets and per-antenna power constraints
(Institute of Electrical and Electronics Engineers (IEEE), 2025-04-29)
Article
Open AccessDesigning energy-efficient beamformers is a major challenge to the deployment of battery-powered devices transmitting short data packets at millimeter-wave frequencies. In general, directly maximizing energy efficiency ... -
Deep learning-based UWB-IMU data fusion for indoor positioning in industrial scenario
(2025-05-05)
Article
Open AccessAccurate and precise wireless infrastructure-based positioning systems become crucial as industries move towards flexible, portable, and autonomous transportation systems such as Automated Guided Vehicles (AGVs). ... -
Singular detection in noncoherent communications
(2025-04)
Article
Open AccessThis paper proposes a general analysis of codeword detection in noncoherent communications. Motivated by the existence of error floors in various regimes, fundamental characteristics of signal design are investigated. In ... -
Conditional dependence via U-Statistics pruning
(2025-02-06)
Article
Open AccessThe problem of measuring conditional dependence between two random phenomena arises when a third one (a confounder) has a potential influence on the amount of information between them. A typical issue in this challenging ... -
Development of attention-based prediction models for all-cause mortality, home care need, and nursing home admission in ageing adults in Spain using longitudinal electronic health record data
(Springer, 2025-01-25)
Article
Open AccessPredicting health-related outcomes can help with proactive healthcare planning and resource management. This is especially important on the older population, an age group growing in the coming decades. Considering longitudinal ... -
Robust design of reconfigurable intelligent surfaces for parameter estimation in MTC
(2025-03-19)
Article
Open AccessThis paper introduces a reconfigurable intelligent surface (RIS) to support parameter estimation in machine-type communications (MTC). We focus on a network where single-antenna sensors transmit spatially correlated ... -
Use of attention maps to enrich discriminability in deep learning prediction models using longitudinal data from electronic health records
(Multidisciplinary Digital Publishing Institute, 2025-01-01)
Article
Open AccessBackground: In predictive modelling, particularly in fields such as healthcare, the importance of understanding the model’s behaviour rivals, if not surpasses, that of discriminability. To this end, attention mechanisms ... -
EMVC-2: an efficient single-nucleotide variant caller based on expectation maximization
(2024-03-04)
Article
Open AccessMotivation: Single-nucleotide variants (SNVs) are the most common type of genetic variation in the human genome. Accurate and efficient detection of SNVs from next-generation sequencing (NGS) data is essential for various ... -
Parametric minimum error entropy criterion: A case study in blind sensor fusion and regression problems
(2024-10-30)
Article
Open AccessThe purpose of this article is to present the Parametric Minimum Error Entropy (PMEE) principle and to show a case study of the proposed criterion in a blind sensor fusion and regression problem. This case study consists ... -
Online joint graph topology and dictionary learning for enhanced data representation
(2024-07-23)
Article
Restricted access - publisher's policyLaplacian-Regularized Dictionary Learning (LRDL) demonstrates remarkable performance in capturing structured representations from data by leveraging underlying graph information. However, in real-world scenarios, the graph ... -
On the convergence of block majorization-minimization algorithms on the grassmann manifold
(2024)
Article
Open AccessThe Majorization-Minimization (MM) framework is widely used to derive efficient algorithms for specific problems that require the optimization of a cost function (which can be convex or not). It is based on a sequential ...