Artículos (Teoría de la Señal y Comunicaciones)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/11422

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Thread Counting in Plain Weave for Old Paintings Using Regression Deep Learning Models
(Springer, 2025) Delgado Bejarano, Antonio; Murillo Fuentes, Juan José; Carcelén-Alba, Laura; Teoría de la Señal y Comunicaciones; Junta de Andalucía; Ministerio de Ciencia e Innovación (MICIN). España
In this paper, we introduce a novel algorithm designed to improve thread density estimation in canvas analysis. Our approach incorporates three major contributions. First, we eliminate the need for post-segmentation processing by integrating regression techniques, enabling the deep learning (DL) model to directly compute thread density. This does not only reduce computational time but also shifts the training focus from locating crossing points to minimizing thread counting errors, thereby enhancing accuracy. We develop and rigorously evaluate various models, selecting the one with optimal performance through a hyperparameter search. Second, we refine the data generation process by dynamically adjusting filter lengths based on initial thread density estimates and incorporating equalization. We also enhance data augmentation. Third, we implement semi-supervised training to expand the dataset and fine-tune model weights. This involves incorporating new inputs into the training set when both the DL model and Fourier transform yield similar density estimates for new paintings. Our proposed algorithm demonstrates superior performance in thread density error reduction and operational efficiency compared to previous DL segmentation solutions for masterpieces from Ribera, Velázquez, or Poussin. Additionally, it has been effectively applied to identify fabric matches between canvases attributed to different authors, showcasing its practical applicability in art analysis.
Development and Validation in Porcine and Human Models of a Bioimpedance Spectroscopy System for the Objective Assessment of Kidney Graft Viability
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Naranjo Hernández, David; Reina Tosina, Luis Javier; Roa Romero, Laura María; Barbarov-Rostán, Gerardo; Calvillo Arbizu, Jorge; Talaminos Barroso, Alejandro; Pérez Valdivia, Miguel Ángel; Medina López, Rafael; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Universidad de Sevilla. Departamento de Ingeniería Telemática; Universidad de Sevilla. Departamento de Medicina; Universidad de Sevilla. Departamento de Cirugía; Fundación Mutua Madrileña; Junta de Andalucía
This work presents an innovative bioimpedance spectroscopy device, developed as a support tool for decision-making during the evaluation of kidney viability for renal transplantation. Given the increasing demand for organs and the need to optimize donation criteria, the precise and objective assessment of renal graft functionality has become crucial. The device, based on a modular design and adapted to the surgical environment, uses a novel Cole model with a frequency-dependent membrane capacitance, which improves measurement accuracy and repeatability compared to conventional models. Adapting the device for operating room usege involved overcoming significant challenges, such as the need for sterilization and a visual, tactile and acoustic user interface that facilitates device usability. Optimizing the sensing stage has minimized the influence of measurement artifacts, which is crucial for obtaining accurate and representative measurements of renal tissue bioelectrical properties. In addition, a rigorous electrode sterilization protocol was designed, ensuring asepsis during the procedure. The results of tests on porcine renal models demonstrated the device’s ability to monitor pathophysiological changes associated with renal ischemia, with a notable improvement against measurement repeatability.
Simultaneous Analysis of Early Components P1 and N1 and Phase and Non-Phase Alpha Activities Associated with Word Recall
(MDPI, 2025) Vázquez Marrufo, Manuel; Navarro Martos, Remedios; Narbona González, Natividad; Martín Clemente, Rubén; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Universidad de Sevilla. Departamento de Psicología Experimental
The study of non-phase modulation of different frequencies in the human electroencephalography (EEG) is revealing new mechanisms involved in information processing. In particular, it has been described that the alpha band, through a desynchronization of its non-phase component, could represent a mechanism for sensory gain in visual stimulus processing. One key question to address is whether this activity can be modulated (increased) by the recall of a previously memorized stimulus. The objective of this study is to answer this question by recording EEG activity with 58 electrodes and applying time-frequency analysis techniques (Temporal Spectral Evolution and the Hilbert Transform) in a sample of 27 human participants during a word recall task. The results of the study showed an increase in alpha phase modulation for recalled words compared to not recalled words, which included modulation of the P1 component. Additionally, alpha non-phase modulation also increased for recalled words, suggesting that the enhanced P1 component response could, in fact, be an indirect result of the attenuation of background neural noise, as proposed by the sensory gain hypothesis.
Addressing the sources of inter-subject variability in E-field parameters in anodal tDCS stimulation over motor cortical network
(IOP PUBLISHING LTD, 2024) Franco-Rosado, Pablo; Callejón Leblic, María Amparo; Reina Tosina, Luis Javier; Roa Romero, Laura María; Martín Rodríguez, Juan Francisco; Mir Rivera, Pablo; Universidad de Sevilla. Departamento de Psicología Experimental; Universidad de Sevilla. Departamento de Medicina; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Ciencia e Innovación (MICIN). España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Junta de Andalucía
Objetive: . Although transcranial direct current stimulation constitutes a non-invasive neuromodulation technique with promising results in a great variety of applications, its clinical implementation is compromised by the high inter-subject variability reported. This study aims to analyze the inter-subject variability in electric fields (E-fields) over regions of the cortical motor network under two electrode montages: the classical C3Fp2 and an alternative P3F3, which confines more the E-field over this region. Approach. Computational models of the head of 98 healthy subjects were developed to simulate the E-field under both montages. E-field parameters such as magnitude, focality and orientation were calculated over three regions of interest (ROI): M1S1, supplementary motor area (SMA) and preSMA. The role of anatomical characteristics as a source of inter-subject variability on E-field parameters and individualized stimulation intensity were addressed using linear mixed-effect models.Main results. P3F3 showed a more confined E-field distribution over M1S1 than C3Fp2; the latter elicited higher E-fields over supplementary motor areas. Both montages showed high inter-subject variability, especially for the normal component over C3Fp2. Skin, bone and CSF ROI volumes showed a negative association with E-field magnitude irrespective of montage. Grey matter volume and montage were the main sources of variability for focality. The curvature of gyri was found to be significantly associated with the variability of normal E-fields.Significance. Computational modeling proves useful in the assessment of E-field variability. Our simulations predict significant differences in E-field magnitude and focality for C3Fp2 and P3F3. However, anatomical characteristics were also found to be significant sources of E-field variability irrespective of electrode montage. The normal E-field component better captured the individual variability and low rate of responder subjects observed in experimental studies.
Symbol constellation predistortion for DCO-OFDM visible light communications system linearization
(Elsevier, 2025-10) Oria Oria, Ana Cinta; Becerra González, Juan Antonio; Madero Ayora, María José; Baena Lecuyer, Vicente; Crespo Cadenas, Carlos; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Universidad de Sevilla. TIC192: Ingeniería Electrónica; Universidad de Sevilla. TIC158: Sistemas de Radiocomunicación
Visible Light Communication (VLC) systems face significant challenges due to the inherent nonlinear characteristics of light emitting diodes (LEDs), which cause distortion in the transmitted DCO-OFDM signals. This signal quality degradation can be lower forcing a large input power back-off (IBO), but leading to an inefficient use of the LEDs. In this work, we propose a predistortion technique, referred to as constellation predistorter (CPD), based on a novel frequency-domain algorithm for the linearization of OFDM signals in VLC systems. The CPD operates on the signal constellation and is based on applying a Bayesian pursuit to obtain a sparse memory polynomial (MP) model matrix. For comparison purposes, this method has been compared to the MP-based time-domain digital predistorter (DPD). The linearization performance of the CPD is measured in terms of the error vector magnitude (EVM) and illumination-to-communication conversion efficiency (ICE) parameters. With the proposed predistorter, we achieve a significant IBO reduction as large as 7.6 dB, enhancing the efficiency of VLC systems, or a nearly 62% decrease in the EVM for a fixed IBO, which represents a substantial reduction in signal distortion and an improvement in ICE.
Decoupling Alpha Desynchronization from Neural Resource Use: Evidence from Cognitive Load Modulation
(MDPI, 2025) Vázquez Marrufo, Manuel; Caballero Díaz, Rocío; Sarrias Arrabal, Esteban; Martín Clemente, Rubén; Universidad de Sevilla. Departamento de Psicología Experimental; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Economía y Competitividad (MINECO). España; Universidad de Sevilla
In prior studies, desynchronization of the induced alpha band (non-phase-locked but time-locked) has been observed across various cognitive tasks. Proposed hypotheses for the cognitive role of this alpha decrement include neural activation, an inhibition/timing mechanism, or a reduction in “neural noise”. This study aimed to examine the effect of cognitive load on induced alpha activity using two versions of a go/no-go visual task: a single-target (ST) version with one target and one distractor, and a double-target (DT) version with two targets and two distractors. EEG was recorded from 58 electrodes, and Temporal Spectral Evolution (TSE) was used for time–frequency analysis. Behavioral results revealed faster reaction times in the ST task compared to the DT task. The P3 component displayed delayed latency and reduced amplitude under increased cognitive load, consistent with prior findings. However, the latencies and amplitudes of evoked and induced alpha responses were unaffected by cognitive load. This suggests that increased alpha desynchronization in subjects with cognitive impairment should not be interpreted as enhanced neural resource recruitment due to task difficulty. Instead, it may reflect other mechanisms unrelated to cognitive load differences in task performance.
Reliability analysis of individual visual P1 and N1 maps indicates the heterogeneous topographies involved in early visual processing among human subjects
(Elsevier, 2021) Vázquez Marrufo, Manuel; Del Barco Gavala, Alberto; Galvao Carmona, Alejandro; Martín Clemente, Rubén; Universidad de Sevilla. Departamento de Psicología Experimental; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Economía y Competitividad (MINECO). España
There is a lack of studies regarding the reliability of the event-related components (ERPs) of an electroencephalogram (EEG) used to assess cognitive processing in human subjects. To explore the reliability scores for the P1 and N1 components in two sessions (separated by an average of 116 days), twenty subjects performed a visual lateralized detection paradigm and EEG recording (58 channels) were employed. The session factor did not modulate the P1/N1 latencies. The visual field factor (left (LVF) or right (RVF)) was a determinant for the P1 and N1 topographical distributions as shown in previous studies. Moreover, topographical maps of the grand average showed a very strong correlation level between sessions (>0.9). Finally, individual maps demonstrated that the classic contralateral pattern for the P1 and N1 components was not always present in all subjects. In particular, compared to the N1 component, the P1 component exhibited a more complex set of individual topographical distributions, revealing that some steps are more heterogeneous among human subjects in early visual processing.
Driving Cycle Synthesis, Aiming for Realness, by Extending Real-World Driving Databases
(Institute of Electrical and Electronics Engineers (IEEE), 2022) Sennefelder, Roman Michael; Micek, Petr; Martín Clemente, Rubén; Carrión Risquez, Jesús; González Carvajal, Ramón; Carrillo-Castrillo, Jesús Antonio; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Consejería de Economía, Conocimiento, Empresas y Universidad, Junta de Andalucía; Universidad de Sevilla. TIC203: Ingeniería Biomédica
In order to transform conventional buses into electric ones, exact knowledge of the energy consumption of the vehicles is essential. Furthermore, for a proper design of the transition and to avoid inefficiencies and excessive costs, this information must be adjusted to real operating scenarios. However, a recurring problem in this context is the lack of data to address all these issues. Previous studies have focused on the use of standard driving cycles or on the synthesis of cycles from a single route. This paper presents a methodology for extending real-world driving databases to perform massive simulations, thereby narrowing the confidence interval of estimates. As a case study, the method was applied to a municipal bus operator’s database in a project to assess the feasibility of retrofitting a diesel to an electric bus. The proposed framework is useful for generating a valid database for research on energy consumption distribution and powertrain optimization, as well as to support public transport bus operators and manufacturers.
A Reduced-Complexity Direct Learning Architecture for Digital Predistortion Through Iterative Pseudoinverse Calculation
(Institute of Electrical and Electronics Engineers (IEEE), 2021-08) Becerra González, Juan Antonio; Pérez Hernández, Abraham; Madero Ayora, María José; Crespo Cadenas, Carlos; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Universidad de Sevilla. TIC158: Sistemas de Radiotelecomunicación
In this letter, a novel approach is proposed for digital predistortion (DPD) with direct learning architecture (DLA). Regression of a Volterra behavioral model requires the pseudoinverse of a matrix, which needs many resources due to the inverse operation when the Moore-Penrose pseudoinverse is used. This work substitutes the pseudoinverse calculation by a polynomial expansion (PE) method to obtain a polynomial expansion direct learning architecture (PE-DLA), which attains a pseudoinverse in an iterative fashion avoiding the inverse operation and consequently reducing the algorithm computational complexity. Experimental results show that the number of iterations in the PE-DLA affects the convergence speed. The proposal is benchmarked against other state-of-the-art approaches such as the classic DLA and the covariance matrix DLA (CM-DLA) in the DPD of a commercial class AB power amplifier, concluding that the linearization performance of the current proposal is equivalent to others while featuring simple operations.
Generalized Exponentiated Gradient Algorithms and Their Application to On-Line Portfolio Selection
(Institute of Electrical and Electronics Engineers (IEEE), 2024-12-19) Cichocki, Andrzej; Cruces Álvarez, Sergio Antonio; Sarmiento Vega, María Auxiliadora; Tanaka, Toshihisa; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Agencia Estatal de Investigación. España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Plan Andaluz de Investigación, Desarrollo e Innovación 2020 (PAIDI); Universidad de Sevilla. TIC246: Tecnologías de aprendizaje automático y procesado digital de la información.
Stochastic gradient descent (SGD) and exponentiated gradient (EG) update methods are widely used in signal processing and machine learning. This study introduces a novel family of generalized Exponentiated Gradient updates (EGAB) derived from the alpha-beta (AB) divergence regularization. The EGAB framework provides enhanced flexibility for processing data with varying distributions, thanks to the tunable hyperparameters of the AB divergence. We explore the applicability of these updates in online portfolio selection (OLPS) for financial markets with the goal of developing algorithms that achieve high risk-adjusted returns, even under relatively high transaction costs. The proposed EGAB algorithms are developed using constrained gradient optimization with regularization terms, demonstrating their versatility in OLPS by unifying the directional search of various algorithms and enabling interpolation between them. Our analysis and extensive computer simulations reveal that EGAB updates outperform existing OLPS algorithms, delivering good results on several performance metrics, such as cumulative return, average excess return, Sharpe ratio, and Calmar ratio, especially when transaction costs are significant. In conclusion, this study introduces a new family of exponentiated gradient updates and demonstrates their flexibility and effectiveness through extensive simulations across a wide range of real-world financial datasets.
Complex Gaussian Processes for Regression and Their Connection to WLMMSE
(Institute of Electrical and Electronics Engineers (IEEE), 2024-12) Boloix Tortosa, Rafael; Murillo Fuentes, Juan José; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Ciencia, Innovación y Universidades (MICINN). España; European Commission (EC); Universidad de Sevilla. TIC155: Tratamiento de Señales y Comunicaciones
The Gaussian process (GP) is a well-established Bayesian nonparametric tool for inference in nonlinear estimation problems. When GPs are used for regression, the goal is to estimate a target signal y from an input vector x without assuming that they are linearly related, but with a probabilistic model p(y|x) that is Gaussian distributed. Therefore, GPs can be understood as a natural nonlinear extension to MMSE estimation. For real-valued GPs, this has been analyzed in the existing literature, and it is concluded that they are the natural nonlinear Bayesian extension to the linear minimum mean-squared error (LMMSE) estimation. In this letter, we show that, consequently, complex-valued GP regression (GPR) models are the natural nonlinear Bayesian extension of the widely linear minimum mean squared-error (WLMMSE) estimation. As in the real-valued case, complex-valued GPs are able to better model many regression problems by making use of the information that the complementary kernel or pseudo-kernel provides.
Features identification for automatic burn classification
(Elsevier, 2015-12) Serrano Gotarredona, María del Carmen ; Boloix Tortosa, Rafael; Gómez Cía, Tomás; Acha Piñero, Begoña; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Junta de Andalucía; Universidad de Sevilla. TIC155: Tratamiento de Señales y Comunicaciones
Purpose In this paper an automatic system to diagnose burn depths based on colour digital photographs is presented. Justification: There is a low success rate in the determination of burn depth for inexperienced surgeons (around 50%), which rises to the range from 64 to 76% for experienced surgeons. In order to establish the first treatment, which is crucial for the patient evolution, the determination of the burn depth is one of the main steps. As the cost of maintaining a Burn Unit is very high, it would be desirable to have an automatic system to give a first assessment in local medical centres or at the emergency, where there is a lack of specialists. Method To this aim a psychophysical experiment to determine the physical characteristics that physicians employ to diagnose a burn depth is described. A Multidimensional Scaling Analysis (MDS) is then applied to the data obtained from the experiment in order to identify these physical features. Subsequently, these characteristics are translated into mathematical features. Finally, via a classifier (Support Vector Machine) and a feature selection method, the discriminant power of these mathematical features to distinguish among burn depths is analysed, and the subset of features that better estimates the burn depth is selected. Results A success rate of 79.73% was obtained when burns were classified as those which needed grafts and those which did not. Conclusions Results validate the ability of the features extracted from the psychophysical experiment to classify burns into their depths.
Implementation of Alternating Direction Method of Multipliers for Solving Power Amplifier Linearization Problem: Theoretical Foundations and Proof of Concept
(Institute of Electrical and Electronics Engineers (IEEE), 2024) Marqués Valderrama, Elías; Becerra González, Juan Antonio; Madero Ayora, María José; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Universidad de Sevilla. TIC158: Sistemas de Radiocomunicación
In this work, a formulation of alternating direction method of multipliers (ADMM) for addressing power amplifiers (PA) modeling and linearization problems is presented. The proposal consists on leveraging the implicit redundancy of the equations in order to achieve a distributed architecture. A detailed theoretical formulation of the method is provided in order to get a better comprehension of its advantages and the approach to integrating the technique in the standard direct learning architecture scheme for digital predistortion. In addition, a discussion on how the implicit regularization helps to deal with numerical problems is presented. It is proven that the implicit regression for the modeling and linearization of PAs can be carried out in a distributed fashion with similar accuracy, enabling the use of resource-constrained devices for digital predistortion. Furthermore, a computational assessment is presented for measuring in terms of arithmetic operations how simpler the devices that implement the proposed ADMM can be, compared with the classical least squares (LS) data-centralized approach. A proof of concept with three scenarios is included: the first two scenarios feature a commercial PA driven by 5G-NR signals with a bandwidth of 30 MHz, and the third scenario involves a commercial Doherty PA with a 100-MHz signal. In a first scenario, experimental results show that an ADMM implementation of a digital predistorter can achieve the same performance as the classical LS solution. The benefits of the proposed regularization are examined by assessing ADMM in a second scenario characterized by significant numerical instabilities. Finally, the robustness of the technique is illustrated through the linearization of the Doherty PA with a 100-MHz OFDM signal.
Smart Bioimpedance Device for the Assessment of Peripheral Muscles in Patients with COPD
(Multidisciplinary Digital Publishing Institute (MDPI), 2024-07) Naranjo Hernández, David; Reina Tosina, Luis Javier; Roa Romero, Laura María; Barbarov-Rostán, Gerardo; Ortega Ruiz, Francisco; Cejudo Ramos, Pilar; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Junta de Andalucía; Fundación Mutua Madrileña; Universidad de Sevilla. TIC203: Ingeniería Biomédica
Muscle dysfunction and muscle atrophy are common complications resulting from Chronic Obstructive Pulmonary Disease (COPD). The evaluation of the peripheral muscles can be carried out through the assessment of their structural components from ultrasound images or their functional components through isometric and isotonic strength tests. This evaluation, performed mainly on the quadriceps muscle, is not only of great interest for diagnosis, prognosis and monitoring of COPD, but also for the evaluation of the benefits of therapeutic interventions. In this work, bioimpedance spectroscopy technology is proposed as a low-cost and easy-to-use alternative for the evaluation of peripheral muscles, becoming a feasible alternative to ultrasound images and strength tests for their application in routine clinical practice. For this purpose, a laboratory prototype of a bioimpedance device has been adapted to perform segmental measurements in the quadriceps region. The validation results obtained in a pseudo-randomized study in patients with COPD in a controlled clinical environment which involved 33 volunteers confirm the correlation and correspondence of the bioimpedance parameters with respect to the structural and functional parameters of the quadriceps muscle, making it possible to propose a set of prediction equations. The main contribution of this manuscript is the discovery of a linear relationship between quadriceps muscle properties and the bioimpedance Cole model parameters, reaching a correlation of 0.69 and an average error of less than 0.2 cm regarding the thickness of the quadriceps estimations from ultrasound images, and a correlation of 0.77 and an average error of 3.9 kg regarding the isometric strength of the quadriceps muscle.
LDA via L1-PCA of Whitened Data
(Institute of Electrical and Electronics Engineers (IEEE), 2020) Martín Clemente, Rubén; Zarzoso, Vicente; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Economía y Competitividad (MINECO). España; Universidad de Sevilla. TIC203: Ingeniería Biomédica
Principal component analysis (PCA) and Fisher's linear discriminant analysis (LDA) are widespread techniques in data analysis and pattern recognition. Recently, the L1-norm has been proposed as an alternative criterion to classical L2-norm in PCA, drawing considerable research interest on account of its increased robustness to outliers. The present work proves that, combined with a whitening preprocessing step, L1-PCA can perform LDA in an unsupervised manner, i.e., sparing the need for labelled data. Rigorous proof is given in the case of data drawn from a mixture of Gaussians. A number of numerical experiments on synthetic as well as real data confirm the theoretical findings.
A full-head model to investigate intra and extracochlear electric fields in cochlear implant stimulation
(Institute of Physics, 2024-08-07) Callejón Leblic, María Amparo; Lazo Maestre, Manuel; Fratter, A.; Ropero Romero, Francisco; Sánchez Gómez, Serafín; Reina Tosina, Luis Javier; Universidad de Sevilla. Departamento de Cirugía; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Ciencia e Innovación (MICIN). España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Junta de Andalucía
Objective. Despite the widespread use and technical improvement of cochlear implant (CI) devices over past decades, further research into the bioelectric bases of CI stimulation is still needed. Various stimulation modes implemented by different CI manufacturers coexist, but their true clinical benefit remains unclear, probably due to the high inter-subject variability reported, which makes the prediction of CI outcomes and the optimal fitting of stimulation parameters challenging. A highly detailed full-head model that includes a cochlea and an electrode array is developed in this study to emulate intracochlear voltages and extracochlear current pathways through the head in CI stimulation. Approach. Simulations based on the finite element method were conducted under monopolar, bipolar, tripolar (TP), and partial TP modes, as well as for apical, medial, and basal electrodes. Variables simulated included: intracochlear voltages, electric field (EF) decay, electric potentials at the scalp and extracochlear currents through the head. To better understand CI side effects such as facial nerve stimulation, caused by spurious current leakage out from the cochlea, special emphasis is given to the analysis of the EF over the facial nerve. Main results. The model reasonably predicts EF magnitudes and trends previously reported in CI users. New relevant extracochlear current pathways through the head and brain tissues have been identified. Simulated results also show differences in the magnitude and distribution of the EF through different segments of the facial nerve upon different stimulation modes and electrodes, dependent on nerve and bone tissue conductivities. Significance. Full-head models prove useful tools to model intra and extracochlear EFs in CI stimulation. Our findings could prove useful in the design of future experimental studies to contrast FNS mechanisms upon stimulation of different electrodes and CI modes. The full-head model developed is freely available for the CI community for further research and use.
Blind Low Complexity Time-Of-Arrival Estimation Algorithm for UWB Signals
(Institute of Electrical and Electronics Engineers (IEEE), 2005-06) Boloix Tortosa, Rafael; Arias de Reyna Domínguez, Eva María; Murillo Fuentes, Juan José; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Educación y Ciencia (MEC). España; Junta de Andalucía; Universidad de Sevilla. TIC155: Tratamiento de Señales y Comunicaciones
This letter presents a novel time-of-arrival (TOA) blind estimation technique for ultra wideband energy detection receivers with reduced complexity. The proposed method is blind in the sense that it does not exploit any information about channel or noise power. This new approach is based on a set of approximations of the exact likelihood function (ELF) of the observed energy. Even though these approximations achieve an important reduction of complexity, the shape of the new approximated function is accurate enough compared to the ELF. Application of a threshold to the differential of the approximated log-likelihood function completes the procedure. Simulations show that the performance of the proposed method in terms of the cumulative distribution function of the estimation error approaches that of a method based on the ELF and a genie-aided algorithm with perfect knowledge of the optimal threshold.
De-Randomization of MAC Addresses Using Fingerprints and RSSI with ML for Wi-Fi Analytics
(IEEE, 2024) Pérez Hernández, Abraham; Barreras Martín, Maydelis N.; Becerra González, Juan Antonio; Madero Ayora, María José; Aguilera Bonet, Pablo; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Universidad de Sevilla. TIC158: Sistemas de Radiocomunicación
Media Access Control (MAC) address randomization causes significant distortion and data loss in Wi-Fi analytics systems, becoming a real challenge for building services based on tracking, location, and presence data. This study aims to mitigate this problem by combining two key points: the construction of a quasi-unique, stable, reliable, and anonymous identifier for non-connected Wi-Fi devices, and the inability of Wi-Fi devices to deliberately change the physical conditions of the connection. We propose a new system that builds identifiers based on the capabilities and information elements announced within the probe request management frames, and consequently applies unsupervised machine learning techniques in the multidimensional Received Signal Strength Indicator (RSSI) space. Experimental tests in a real-world environment were conducted, and the results of this extensive field study demonstrated that the proposed system achieves high accuracy in identifying and tracking non-connected Wi-Fi devices in these challenging scenarios, even in the presence of MAC randomization. Our findings suggest that the proposed system has a significant potential for enhancing building services that rely on Wi-Fi data.
Hybrid higher-order statistics learning in multiuser detection
(Institute of Electrical and Electronics Engineers (IEEE), 2004-11) Caamano, Antonio J.; Boloix Tortosa, Rafael; Ramos, Javier; Murillo Fuentes, Juan José; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Ciencia Y Tecnología (MCYT). España; Universidad de Sevilla. TIC-155: Tratamiento de señales y comunicaciones
In this paper, we explore the significance of second- and higher-order statistics learning in communication systems. The final goal in spread-spectrum communication systems is to receive a signal of interest completely free from interference caused by other concurrent signals. To achieve this end, we exploit the structure of the interference by designing second-order statistics detectors, such as the minimum square error, in conjunction with higher-order statistics (HOS) techniques, such as the blind source separation (BSS). This hybrid higher-order statistics (HyHOS) approach enables us to alleviate BSS algorithms of one of their main problems, that is, their sensitiveness to high levels of noise. In addition, we benefit from remarkable properties of BSS in learning such as fast learning (superefficiency) and independence of the initial settings of the problem (equivariance). We successfully applied the results of this approach to the design of multiuser detectors in code-division multiple access channels. © 2004 IEEE.
Strict separability and identifiability of a class of ICA models
(2010-03) Murillo Fuentes, Juan José; Boloix Tortosa, Rafael; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Ciencia e Innovación (MICIN). España; Universidad de Sevilla. TIC-155: Tratamiento de señales y comunicaciones
In this letter we focus on the application of independent component analysis (ICA) to a class of overdetermined blind source separation (BSS) problems. The mixing matrix in the BSS model is the product of an unknown square diagonal matrix and a projection matrix. The last matrix performs a known projection to the same or larger dimensional space. We demonstrate the conditions for the model to be strictly separable and identifiable under the statistical independence condition, paying attention to permutations and relative scalings. These results find application, e.g., in the channel estimation of ZP-OFDM and Precoded-OFDM systems

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