DTSC - GTSA - Capítulos de Monografías

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Modeling phone call durations via switching Poisson processes with applications in mental health
(IEEE, 2020-10-20) Bonilla Escribano, Pablo; Ramírez García, David; Artés Rodríguez, Antonio
This work models phone call durations via switching Poisson point processes. This kind of processes is composed by two intertwined intensity functions: one models the start of a call, whereas the other one models when the call ends. Thus, the call duration is obtained from the inverse of the intensity function of finishing a call. Additionally, to model the circadian rhythm present in human behavior, we shall use a (pos-itive) truncated Fourier series as the parametric form of the intensities. Finally, the maximum likelihood estimates of the intensity functions are obtained using a trust region method and the performance is evaluated on synthetic and real data, showing good results.
Hidden Markov Models for Activity Detection in Atrial Fibrillation Electrograms
(IEEE, 2020-09-13) Ríos Muñoz, Gonzalo Ricardo; Moreno Pino, Fernando; Soto, Nina; Martínez Olmos, Pablo; Artés Rodríguez, Antonio; Fernández Avilés, Francisco; Arenal, Ángel; Comunidad de Madrid; Ministerio de Ciencia, Innovación y Universidades (España)
Activity detection in atrial fibrillation (AF) electrograms (EGMs) is a key concept to understand the mechanisms of this frequent arrhythmia and design new strategies for its treatment. We present a new method that employs Hidden Markov Models (HMMs) to identify activity presence in bipolar EGMs. The method is fully unsupervised and hence it does not require labeled training data. The HMM activity detection method was validated and compared to the non-linear energy operator (NLEO) method for a set of manually annotated EGMs. The HMM performed better than the NLEO and exhibited more robustness in the presence of low voltage fragmented EGMs.
Particle Filter Tracking of Complex Stochastic Systems Applied to In Silico Wavefront Propagation
(IEEE, 2019-06-24) Ríos Muñoz, Gonzalo Ricardo; Artés Rodríguez, Antonio; Míguez Arenas, Joaquín; Comunidad de Madrid; Ministerio de Economía y Competitividad (España)
A high dimensional tracking system based on the FithzHugh-Nagumo (FH-N) equations emulating the biological excitation and propagation dynamics of the action potential across cardiac cells is proposed. The modified FH-N model tracks the electric cardiac wavefronts on a tissue, emulating an approximated atrial fibrillation scenario. Bayesian tracking is achieved with two particle filter (PF) schemes: a sequential Auxiliary PF (APF) and a parallelized method, Independent APF (IAPF). The numerical results of the two examples, involving both estimation errors and running times, provide numerical evidence that support the theoretical findings.
Patient-Tailored In Silico 3D Simulations and Models From Electroanatomical Maps of the Left Atrium
(IEEE, 2019-06-24) Ríos Muñoz, Gonzalo Ricardo; Rocher, Sara; Artés Rodríguez, Antonio; Arenal, Ángel; Saiz, Javier; Sánchez, Carlos; Comunidad de Madrid; Ministerio de Economía y Competitividad (España)
The mechanisms underlying atrial fibrillation (AF) are still under debate, making treatments for this arrhythmia remain suboptimal, with most treatments applied in a standard fashion with no patient personalization. Recent technological advances in electroanatomical mapping (EAM) using multi-electrode catheter allow the physicians to better characterize the substrate, thanks to a better spatial resolution and higher density of acquisition points. Taking advantage of this technology, we describe a workflow to build personalized electrophysiological atrial models for AF patients. We seek to better predict the outcome of a treatment and study the AF problem in a more specific scenario. We generated physiological 3D models from the EAM data using hexahedral meshing of element size 300μm, and added fiber orientation based on a generic model. We used the local activation time (LAT) maps performed in sinus rhythm (SR) to estimate the conduction velocity (CV) of the regions in the atrium with a new method that combines the LATs of neighboring tissue as the average CV of triplets of points. We also characterized the cellular model by Maleckar et al. in terms of longitudinal conductivity and CV to personalize the atrial models. We were able to simulate SR and AF scenarios on the personalized models, and we generated a database of atrial models for future analysis.
Causality analysis of atrial fibrillation electrograms
(IEEE, 2015-09-06) Luengo García, David; Ríos Muñoz, Gonzalo Ricardo; Elvira Arregui, Víctor; Ministerio de Economía y Competitividad (España)
Multi-channel intracardiac electrocardiograms (electrograms) are sequentially acquired during heart surgery performed on patients with sustained atrial fibrillation (AF) to guide radio frequency catheter ablation. These electrograms are used by cardiologists to determine candidate areas for ablation (e.g., areas corresponding to high dominant frequencies or complex electrograms). In this paper, we introduce a novel hierarchical causality analysis method for the multi-output sequentially acquired electrograms. The causal model obtained provides important information regarding delays among signals as well as the direction and strength of their causal connections. The tool developed may ultimately serve to guide cardiologists towards candidate areas for catheter ablation. Preliminary results on synthetic signals are used to validate the proposed approach.
Scaling laws for many-access channels and unsourced random access
(IEEE, 2022-03-04) Ravikumaran Nair, Jithin; Koch, Tobias Mirco; European Commission; Ministerio de Ciencia e Innovación (España)
In the emerging Internet of Things, a massive number of devices may connect to one common receiver. Consequently, models that study this setting are variants of the classical multiple-access channel where the number of users grows with the blocklength. Roughly, these models can be classified into three groups based on two criteria: the notion of probability of error and whether users use the same codebook. The first group follows the classical notion of probability of error and assumes that users use different codebooks. In the second group, users use different codebooks, but a new notion of probability of error called per-user probability of error is considered. The third group considers the per-user probability of error and that users are restricted to use the same codebook. This group is also known as unsourced random access. For the first and second groups of models, scaling laws that describe the capacity per unit-energy as a function of the order of growth of users were characterized by Ravi and Koch (arxiv.org/abs/2012.10350). In this paper, we first review these results. We then present scaling laws for the third group of models, i.e., unsourced random access.
A High-SNR Normal Approximation for MIMO Rayleigh Block-Fading Channels
(IEEE, 2020-08-24) Qi, Chao; Koch, Tobias Mirco; European Commission; Ministerio de Economía y Competitividad (España)
This paper concerns the maximum coding rate at which a code of given blocklength can be transmitted with a given block-error probability over a non-coherent Rayleigh block-fading channel with multiple transmit and receive antennas (MIMO). In particular, a high-SNR normal approximation of the maximum coding rate is presented, which is proved to become accurate as the signal-to-noise ratio (SNR) and the number of coherence intervals L tend to infinity.
Bursty Wireless Networks of Bounded Capacity
(IEEE, 2020-08-24) Villacrés Estrada, Grace Silvana; Koch, Tobias Mirco; Vázquez Vilar, Gonzalo; European Commission; Ministerio de Economía y Competitividad (España)
The channel capacity of wireless networks Is often studied under the assumption that the communicating nodes have perfect channel-state information and that interference is always present. In this paper, we study the channel capacity of a wireless network without these assumptions, i.e., a bursty noncoherent wireless network where the users are grouped in cells and the base-station features several receive antennas. We demonstrate that the channel capacity is bounded in the signal-to-noise ratio (SNR) when the number of receive antennas is finite and the probability of presence of interference is strictly positive.
Capacity per Unit-Energy of Gaussian Random Many-Access Channels
(IEEE, 2020-08-24) Ravikumaran Nair, Jithin; Koch, Tobias Mirco; European Commission; Ministerio de Economía y Competitividad (España)
We consider a Gaussian multiple-access channel with random user activity where the total number of userslₙ and the average number of active users kₙ may be unbounded. For this channel, we characterize the maximum number of bits that can be transmitted reliably per unit-energy in terms of lₙ and kₙ . We show that if kₙ log lₙ is sublinear in n, then each user can achieve the single-user capacity per unit-energy. Conversely, if kₙ log lₙ is superlinear in n, then the capacity per unit-energy is zero. We further demonstrate that orthogonal-access schemes, which are optimal when all users are active with probability one, can be strictly suboptimal.
Finite-Blocklength Approximations for Noncoherent Rayleigh Block-Fading Channels
(IEEE, 2020-03-30) Lancho Serrano, Alejandro; Östman, Johan; Koch, Tobias Mirco; Vázquez Vilar, Gonzalo; European Commission; Ministerio de Economía y Competitividad (España)
Several emerging wireless communication services and applications have stringent latency requirements, necessitating the transmission of short packets. To obtain performance benchmarks for short-packet wireless communications, it is crucial to study the maximum coding rate as a function of the blocklength, commonly called finite-blocklength analysis. A finiteblocklength analysis can be performed via nonasymptotic bounds or via refined asymptotic approximations. This paper reviews finite-blocklength approximations for the noncoherent Rayleigh block-fading channel. These approximations have negligible computational cost compared to the nonasymptotic bounds and are shown to be accurate for error probabilities as small as 10-8 [super index] and SNRs down to 0 dB.
Saddlepoint Approximations for Noncoherent Single-Antenna Rayleigh Block-Fading Channels
(IEEE, 2019-09-26) Lancho Serrano, Alejandro; Östman, Johan; Durisi, Giuseppe; Koch, Tobias Mirco; Vázquez Vilar, Gonzalo; Comunidad de Madrid; European Commission; Ministerio de Economía y Competitividad (España); Ministerio de Educación, Cultura y Deporte (España)
This paper presents saddlepoint approximations of state-of-the-art converse and achievability bounds for noncoherent, single-antenna, Rayleigh block-fading channels. These approximations can be calculated efficiently and are shown to be accurate for SNR values as small as 0 dB, blocklengths of 168 channel uses or more, and when the channel's coherence interval is not smaller than two. It is demonstrated that the derived approximations recover both the normal approximation and the reliability function of the channel.
Private Index Coding
(IEEE, 2018-08-16) Narayanan, Varun; Ravikumaran Nair, Jithin; Mishra, Vivek K.; Dey, Bikash K.; Karamchandani, Nikhil; Prabhkaran, Vinod M.; European Commission
We study the problem of index coding under the privacy requirement that receivers do not learn anything more than the messages they already have as side information and the message they want from the server. To achieve this private index coding, we consider the use of secret keys that are shared among various subsets of users and the server. We characterize key access structures that allow private index coding. For up to three receivers, we characterize the rate region of transmission and key rates and show that scalar coding is optimal; we also show that scalar linear codes are sub-optimal for four receivers. Furthermore, when no keys are available, we consider a weaker notion of privacy analogous to weak security. Finally, for a different setting in which the server is allowed to send messages exclusively to a subset of users, we study the number of transmissions required to achieve error-free decoding and privacy.
The Role of Interaction and Common Randomness in Two-User Secure Computation
(IEEE, 2018-08) Kurri, Gowtham R.; Ravikumaran Nair, Jithin; Prabhakaran, Vinod M.; European Commission
We consider interactive computation of randomized functions between two users with the following privacy requirement: the interactive communication should not reveal to either user any extra information about the other user's input and output other than what can be inferred from the user's own input and output. We also consider the case where privacy is required against only one of the users. For both cases, we give single-letter expressions for feasibility and optimal rates of communication. Then we discuss the role of common randomness and interaction in both privacy settings.
Saddlepoint approximations of lower and upper bounds to the error probability in channel coding
(IEEE, 2018-03-21) Font Segura, Josep; Vázquez Vilar, Gonzalo; Martínez, Alfonso; Guillén I Fàbregas, Albert; Lancho Serrano, Alejandro; European Commission; Ministerio de Economía y Competitividad (España); Ministerio de Educación, Cultura y Deporte (España)
Saddlepoint approximations of the meta-converse and random-coding union bounds are derived. These bounds accurately characterize the channel coding minimum error probability for symmetric memoryless channels in a wide range of system parameters. The proposed approximations are simple to compute and yield a unified analysis of both hypothesis-testing lower bounds and random-coding upper bounds.
The Error Probability of Generalized Perfect Codes
(IEEE, 2018-08-16) Vazquez Vilar, Gonzalo; Guillén I Fàbregas, Albert; Verdú, Sergio; European Commission; Ministerio de Economía y Competitividad (España)
We introduce a definition of perfect and quasi-perfect codes for symmetric channels parametrized by an auxiliary output distribution. This new definition generalizes previous definitions and encompasses maximum distance separable codes. The error probability of these codes, whenever they exist, is shown to attain the meta-converse lower bound.
Pre-emphasizing Binarized Ensembles to Improve Classification Performance
(Springer, 2017-06-14) Álvarez Pérez, Lorena; Ahachad, Anas; Figueiras, Aníbal; Comunidad de Madrid; Ministerio de Economía y Competitividad (España)
Machine ensembles are learning architectures that offer high expressive capacities and, consequently, remarkable performances. This is due to their high number of trainable parameters.In this paper, we explore and discuss whether binarization techniques are effective to improve standard diversification methods and if a simple additional trick, consisting in weighting the training examples, allows to obtain better results. Experimental results, for three selected classification problems, show that binarization permits that standard direct diversification methods (bagging, in particular) achieve better results, obtaining even more significant performance improvements when pre-emphasizing the training samples. Some research avenues that this finding opens are mentioned in the conclusions.
Saddlepoint Approximation of the Error Probability of Binary Hypothesis Testing
(IEEE, 2018-08-16) Vázquez Vilar, Gonzalo; Guillén i Fàbregas, Albert; Koch, Tobias Mirco; Lancho Serrano, Alejandro
We propose a saddlepoint approximation of the error probability of a binary hypothesis test between two i.i.d. distributions. The approximation is accurate, simple to compute, and yields a unified analysis in different asymptotic regimes. The proposed formulation is used to efficiently compute the meta-converse lower bound for moderate block-lengths in several cases of interest.
Design of Discrete Constellations for Peak-Power-Limited complex Gaussian Channels
(IEEE, 2018-08-16) Huleihel, Wasim; Goldfeld, Ziv; Koch, Tobias Mirco; Madiman, Mokshay; Médard, Muriel; Huleihel, Wasim
The capacity-achieving input distribution of the complex Gaussian channel with both average- and peak-power constraint is known to have a discrete amplitude and a continuous, uniformly-distributed, phase. Practical considerations, however, render the continuous phase inapplicable. This work studies the backoff from capacity induced by discretizing the phase of the input signal. A sufficient condition on the total number of quantization points that guarantees an arbitrarily small backoff is derived, and constellations that attain this guaranteed performance are proposed.
Normal approximations for fading channels
(IEEE, 2018-05-24) Lancho Serrano, Alejandro; Koch, Tobias Mirco; Durisi, Giuseppe
Capacity and outage capacity characterize the maximum coding rate at which reliable communication is feasible when there are no constraints on the packet length. Evaluated for fading channels, they are important performance benchmarks for wireless communication systems. However, the latency of a communication system is proportional to the length of the packets it exchanges, so assuming that there are no constraints on the packet length may be overly optimistic for communication systems with stringent latency constraints. Recently, there has been great interest within the information theory community in characterizing the maximum coding rate for short packet lengths. Research on this topic is often concerned with asymptotic expansions of the coding rate with respect to the packet length, which then give rise to normal approximations. In this paper, we review existing normal approximations for single-antenna Rayleigh block-fading channels and compare them with the high-SNR normal approximation we presented at the 2017 IEEE International Symposium on Information Theory (Lancho, Koch, and Durisi, 2017). We further discuss how these normal approx- imations may help to assess the performance of communication protocols.
On the information dimension rate of stochastic processes
(IEEE, 2017-08-15) Geiger, Bernhard C.; Koch, Tobias Mirco
Jalali and Poor ("Universal compressed sensing," arXiv:1406.7807v3, Jan. 2016) have recently proposed a generalization of Rényi's information dimension to stationary stochastic processes by defining the information dimension of the stochastic process as the information dimension of k samples divided by k in the limit as k →∞ to. This paper proposes an alternative definition of information dimension as the entropy rate of the uniformly-quantized stochastic process divided by minus the logarithm of the quantizer step size 1/m in the limit as m →∞ ; to. It is demonstrated that both definitions are equivalent for stochastic processes that are ψ*-mixing, but that they may differ in general. In particular, it is shown that for Gaussian processes with essentially-bounded power spectral density (PSD), the proposed information dimension equals the Lebesgue measure of the PSD's support. This is in stark contrast to the information dimension proposed by Jalali and Poor, which is 1 if the process's PSD is positive on a set of positive Lebesgue measure, irrespective of its support size.

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