Gregorio Maranon Health Research Institute

Madrid, Spain

Gregorio Maranon Health Research Institute

Madrid, Spain

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Hasija T.,University of Paderborn | Song Y.,Nanyang Technological University | Schreier P.J.,University of Paderborn | Ramirez D.,Charles III University of Madrid | Ramirez D.,Gregorio Maranon Health Research Institute
Conference Record - Asilomar Conference on Signals, Systems and Computers | Year: 2016

We present a scheme for determining the number of signals common to or correlated across multiple data sets. Handling multiple data sets is challenging due to the different possible correlation structures. For two data sets, the signals are either correlated or uncorrelated between the data sets. For multiple data sets, however, there are numerous combinations how the signals can be correlated. Prior studies dealing with multiple data sets all assume a particular correlation structure. In this paper, we present a technique based on a series of hypothesis tests and the bootstrap, which works for arbitrary correlation structure. Numerical results show that the proposed technique correctly detects the number of correlated signals in scenarios where the competition tends to overestimate. © 2016 IEEE.


Luengo D.,Polytechnic University of Valencia | Rios-Munoz G.,Charles III University of Madrid | Rios-Munoz G.,Gregorio Maranon Health Research Institute | Elvira V.,Polytechnic University of Valencia | And 2 more authors.
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings | Year: 2016

Multi-channel intracardiac electrocardiograms (electrograms) are sequentially acquired, at the electrophysiology laboratory, in order to guide radio frequency catheter ablation during heart surgery performed on patients with sustained atrial fibrillation (AF). These electrograms are used by cardiologists to determine candidate areas for ablation (e.g., areas corresponding to high dominant frequencies or complex fractionated electrograms). In this paper, we introduce a novel hierarchical algorithm for causality discovery among these multi-output sequentially acquired electrograms. The causal model obtained provides important information about the propagation of the electrical signals inside the heart, uncovering wavefronts and activation patterns that will serve to increase our knowledge about AF and guide cardiologists towards candidate areas for catheter ablation. Numerical results on synthetic signals, generated using the FitzHugh-Nagumo model, show the good performance of the proposed approach. © 2016 IEEE.


Guzman B.G.,Charles III University of Madrid | Serrano A.L.,Charles III University of Madrid | Serrano A.L.,Gregorio Maranon Health Research Institute | Gil Jimenez V.P.,Charles III University of Madrid
IEEE Transactions on Consumer Electronics | Year: 2015

In this paper, a novel cooperative transmission and reception scheme in Visible Light Communications (VLC) is proposed and evaluated. This new scheme provides improvements and reliability in large indoor scenarios, such as corridors, laboratories, shops or conference rooms, where the coverage needs to be obtained by using different access points when VLC is used. The main idea behind the proposal is a simple cooperative transmission scheme where the receiver terminal will obtain the signal from different access points at the same time. This proposal outperforms traditional VLC schemes, especially in Non-Line-of-Sight reception where around 3 dB of gain, with respect to traditional schemes, can be obtained for unoptimized parameters, and larger than 3 dB could easily be achieved. The cooperation is studied in terms of the percentage of light coming from the main access point and a parameter called sidelobes' amplitude level. The performance is evaluated according to the location within the atto-cell. © 2015 IEEE.


Stinner M.,TU Munich | Olmos P.M.,Charles III University of Madrid | Olmos P.M.,Gregorio Maranon Health Research Institute
IEEE Journal on Selected Areas in Communications | Year: 2016

An analysis of spatially coupled low-density parity-check (SC-LDPC) codes constructed from protographs is proposed. Given the protograph used to generate the SC-LDPC code ensemble, a set of scaling parameters to characterize the average finite-length performance in the waterfall region is computed. The error performance of structured SC-LDPC code ensembles is shown to follow a scaling law similar to that of unstructured randomly constructed SC-LDPC codes. Under a finite-length perspective, some of the most relevant SC-LDPC protograph structures proposed to date are compared. The analysis reveals significant differences in their finite-length scaling behavior, which is corroborated by simulation. Spatially coupled repeat-accumulate codes present excellent finite-length performance, as they outperform in the waterfall region SC-LDPC codes of the same rate and better asymptotic thresholds. © 2015 IEEE.


Koch T.,Charles III University of Madrid | Koch T.,Gregorio Maranon Health Research Institute
IEEE Transactions on Information Theory | Year: 2016

The Shannon lower bound is one of the few lower bounds on the rate-distortion function that holds for a large class of sources. In this paper, which considers exclusively normbased difference distortion measures, it is demonstrated that its gap to the rate-distortion function vanishes as the allowed distortion tends to zero for all sources having finite differential entropy and whose integer part has finite entropy. Conversely, it is demonstrated that if the integer part of the source has infinite entropy, then its rate-distortion function is infinite for every finite distortion level. Thus, the Shannon lower bound provides an asymptotically tight bound on the rate-distortion function if, and only if, the integer part of the source has finite entropy. © 2016 IEEE.


Pries A.,University of Paderborn | Ramirez D.,Charles III University of Madrid | Ramirez D.,Gregorio Maranon Health Research Institute | Schreier P.J.,University of Paderborn
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings | Year: 2016

One approach to spectrum sensing for cognitive radio is the detection of cyclostationarity. We extend an existing multi-antenna detector for cyclostationarity proposed by Ramírez et al. [1], which makes no assumptions about the noise beyond being (temporally) wide-sense stationary. In special cases, the noise could be uncorrelated among antennas, or it could be temporally white. The performance of a general detector can be improved by making use of a priori structural information. We do not, however, require knowledge of the exact values of the temporal or spatial noise covariances. We develop an asymptotic generalized likelihood ratio test and evaluate the performance by simulations. © 2016 IEEE.


Koch T.,Charles III University of Madrid | Koch T.,Gregorio Maranon Health Research Institute | Vazquez-Vilar G.,Charles III University of Madrid | Vazquez-Vilar G.,Gregorio Maranon Health Research Institute
IEEE International Symposium on Information Theory - Proceedings | Year: 2016

We derive a lower bound on the smallest output entropy that can be achieved via scalar quantization of a source with given expected quadratic distortion. As the allowed distortion tends to zero, the bound converges to the output entropy achieved by a uniform quantizer, thereby recovering the result by Gish and Pierce that uniform quantizers are asymptotically optimal. The proposed derivation applies for any memoryless source that has a probability density function (pdf), a finite differential entropy, and whose integer part has a finite entropy. In contrast to Gish and Pierce, we do not require any additional constraints on the continuity or decay of the source pdf. © 2016 IEEE.


Song Y.,University of Paderborn | Schreier P.J.,University of Paderborn | Ramirez D.,Charles III University of Madrid | Ramirez D.,Gregorio Maranon Health Research Institute | Hasija T.,University of Paderborn
Signal Processing | Year: 2016

This paper is concerned with the analysis of correlation between two high-dimensional data sets when there are only few correlated signal components but the number of samples is very small, possibly much smaller than the dimensions of the data. In such a scenario, a principal component analysis (PCA) rank-reduction preprocessing step is commonly performed before applying canonical correlation analysis (CCA). We present simple, yet very effective, approaches to the joint model-order selection of the number of dimensions that should be retained through the PCA step and the number of correlated signals. These approaches are based on reduced-rank versions of the Bartlett-Lawley hypothesis test and the minimum description length information-theoretic criterion. Simulation results show that the techniques perform well for very small sample sizes even in colored noise. © 2016 Elsevier B.V. All rights reserved.


Villacres G.,Charles III University of Madrid | Villacres G.,Gregorio Maranon Health Research Institute | Koch T.,Charles III University of Madrid | Koch T.,Gregorio Maranon Health Research Institute
IEEE International Symposium on Information Theory - Proceedings | Year: 2016

The channel capacity of wireless networks is often studied under the assumption that the communicating nodes have perfect channel-state information (CSI) in the sense that they have access to the fading coefficients in the network. To the best of our knowledge, one of the few works that studies wireless networks without this assumption is by Lozano, Heath, and Andrews. Inter alia, Lozano et al. show that in the absence of perfect CSI, and if the channel inputs are given by the square-root of the transmit power times a power-independent random variable, then the achievable information rate is bounded in the signal-to-noise ratio (SNR). However, such inputs do not necessarily achieve capacity, so one may argue that the information rate is bounded in the SNR because of the suboptimal input distribution. In this paper, it is demonstrated that if the nodes do not cooperate and they all use the same codebook, then the achievable information rate remains bounded in the SNR even if the input distribution is allowed to change arbitrarily with the transmit power. © 2016 IEEE.


Hasija T.,University of Paderborn | Song Y.,University of Paderborn | Schreier P.J.,University of Paderborn | Ramirez D.,Charles III University of Madrid | Ramirez D.,Gregorio Maranon Health Research Institute
IEEE Workshop on Statistical Signal Processing Proceedings | Year: 2016

This paper addresses the problem of detecting the number of signals correlated across multiple data sets with small sample support. While there have been studies involving two data sets, the problem with more than two data sets has been less explored. In this work, a rank-reduced hypothesis test for more than two data sets is presented for scenarios where the number of samples is small compared to the dimensions of the data sets. © 2016 IEEE.

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