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=h\:#8X@"1Arial1Arial1Arial1Arial1 Arial"$"#,##0_);\("$"#,##0\)!"$"#,##0_);[Red]\("$"#,##0\)""$"#,##0.00_);\("$"#,##0.00\)'""$"#,##0.00_);[Red]\("$"#,##0.00\)7*2_("$"* #,##0_);_("$"* \(#,##0\);_("$"* ""_);_(@_).))_(* #,##0_);_(* \(#,##0\);_(* ""_);_(@_)?,:_("$"* #,##0.00_);_("$"* \(#,##0.00\);_("$"* ""??_);_(@_)6+1_(* #,##0.00_);_(* \(#,##0.00\);_(* ""??_);_(@_) + ) , * `gProyectos de I+D+i%nkEstancias y sabticos recogid{lTesis DoctoralesmArtculos en revistastCaptulos de libros%0wConferencias invitadas en con%=xCursos, seminarios y tutorial%JyInformes para las AAPP o sus WzLibrosd{Otras Publicaciones?Ponencia en Congresos̋Creacin de empresasٌKnowHowPatentesRegistros de SoftwareVariedades vegetales
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InternacionalTipo de proyectoEntidad financiadoraNacionalidad EntidadTamao de la entidadFecha concesin
ParticipantesOtros ParticipantesUECUACIONES EN DIFERENCIAS Y APROXIMACION CONSTRUCTIVA: CASO UNIVARIABLE. APLICACIONES%Proyecto coordinado del Plan Nacional0<Proyectos y convenios en convocatorias pblicas competitivas'Ministerio de Economa y CompetitividadESPAADesconocidoDirector: Maria Dolores Barrios Rolania//Participante: Bernardo De La Calle Ysern//Participante: Alejandro Zarzo Altarejos//8MODELOS GENERATIVOS PARA FIBRILACIN AURICULAR (MGFIAR)aLa fibrilacin auricular (FA) es la arritmia cardiaca ms comn, habiendo alcanzado proporciones epidmicas: se estima que en Espaa podra haber 1 milln de personas con FA actualmente, con una previsin de 2 millones de afectados en 2050. Su incidencia es tan elevada que una de cada cuatro personas mayores de cuarenta aos sufrirn FA a lo largo de su vida. No obstante, a pesar de ser una fuente comn de hospitalizacin y un importante factor de riesgo en dolencias agudas y potencialmente mortales (como el infarto o el derrame cerebral), sus causas an no son bien conocidas. Mltiples hiptesis han sido propuestas para su inicializacin y mantenimiento: rotores, mltiples ondas reentrantes, focos ectpicos, etc. Desafortunadamente, el papel de cada uno de estos mecanismos en la FA no est determinado de manera precisa.
La electrocardiografa fue una de las primeras reas en las que se aplic el procesado digital de seales. En el caso de la FA, este se ha concentrado en el anlisis espectral, destacando el uso de la frecuencia dominante para localizar reas de arritmognesis. Esta medida se complementa tpicamente con otros descriptores temporales, como los ndices de fraccionamiento y organizacin. Otras tcnicas, como el anlisis de componentes independientes (ICA), se han utilizado para separar la seal de artefactos y ruido. Sin embargo, ninguna de ellas se ha centrado en desarrollar modelos que permitan profundizar en el conocimiento de la FA y sus causas. El solicitante ha desarrollado recientemente, junto con otros colaboradores (Prof. Antonio Arts, Dr. Javier Va y Dr. Thomas Trigano), modelos descriptivos para electrocardiogramas intracavitales basados en mtodos de aprendizaje de seales dispersas. Esta propuesta pretende ir un paso ms all, desarrollando modelos generativos (basados en procesos Gaussianos y aprendizaje Bayesiano no paramtrico) que permitan profundizar en los mecanismos que generan y sustentan la FA. Como beneficio adicional, estos modelos permitirn, una vez entrenados, generar fcilmente seales sintticas que se podrn utilizar para desarrollar y validar otros algoritmos.Proyectos y convenios de financiacin privadaFundacin BBVA
13/10/2014Director: David Luengo Garcia//SENSOR ROBUSTO(Proyecto del Plan Nacional I+D+i (CICYT)"Ministerio de Ciencia e InnovacinSin nacionalidad&Director: M. Elena Dominguez Jimenez//JCR del ISITtulo de la revistaISSNFactor de impacto JCRInformacin de impactoVolumenDOINmero de revistaDesde la pginaHasta la pginaMesRanking\Bacterially inspired evolution of intelligent systems under constantly changing environmentsThis paper explores the capabilities of openended bioinspired evolutionary construction of intelligent systems under changing environments. We present and analyze extensive results of the bacterial evolutionary system. This system creates 3D environments that simulate real constantly changing environments. Populations of artificial bacteria constantly evolve their inner biological processes in these environments as they perform every action programmed in their life cycle. This results in a decentralized, asynchronous, parallel and selfadapting generalpurpose evolutionary process whose only goal is the survival of the bacterial population under successive, continuously changing environmental conditions. Results show the problem independence and generalpurpose capabilities of the system by making it evolve fuzzy rulebased systems under different environments. Robustness and fault tolerance capabilities are also tested by subjecting the bacterial evolutionary system to sudden changes in the environment. Evolution is openended as there is no need to restart the system when changes take place. Artificial bacteria selfadapt themselves in real time in order to guarantee their survival.
Bacterially inspired evolution of intelligent systems under constantly changing environments. Available from: https://www.researchgate.net/publication/271953141_Bacterially_inspired_evolution_of_intelligent_systems_under_constantly_changing_environments [accessed May 6, 2015].1Soft Computing 143276431,3041910.1007/s005000141319441071 1083SIN MESCAutor: Maria Dolores Barrios Rolania//Autor: Daniel Manrique Gamo//Autor: Jos Mara Font //8Design and analysis of demandadapted railway timetables"JOURNAL OF ADVANCED TRANSPORTATION 019767290,7334810.1002/atr.12612119137"Autor: Alejandro Zarzo Altarejos//FAutor: david canca //Autor: eva barrena //Autor: encarnacion algaba //SEfficient monte carlo methods for multidimensional learning with classifier chainsPATTERN RECOGNITION 003132032,2924710.1016/j.patcog.2013.10.006315351546Autor: David Luengo Garcia//*Autor: jesse read //Autor: luca martino //ARailway Rapid Transit timetables with variable and elastic demandThe aim of this paper is to provide an optimization model which, unlike the majority of previous works, considers a variable demand profile along a whole design day. So, one aspect to stand out in our model is the case of elastic demand, which leads to passengers may select an alternative transportation mode and as a result, income of service providers can be seriously compromised.
The mode choice is modeled using two alternative methods, a sigmoid function and a Logit model which influence the headway calculation. With the purpose of obtaining optimal departure times, a minimization of the loss of passengers is required. Finally, the model is applied to a real case and the computational results are shown.
)Procedia  Social and Behavioral Sciences 18770428
111 (2014)5385480The JentzschSzeg Theorem and Balayage MeasuresSe prueba que para el caso de una funcin analtica el fenmeno de acumulacin de ceros de los polinomios de Taylor sobre la frontera del disco de convergencia no es exclusivo de polinomios extremales sino que se cumple para una clase muy general de polinomios de interpolacinConstructive Approximation 017642761,1694010.1007/s0036501492408307327OCTUBREQ1#Autor: Bernardo De La Calle Ysern//Edicin del LibroEditorial del LibroISBNSerieTtulo del LibroDesde pginaHasta pginaKSimulation of Multipath Fading Channels for Wireless Communication NetworksThe accurate simulation of multipath fading channels is a crucial issue in the development and evaluation of modern wireless communication networks. Since the received signal depends on many fast changing factors, statistical models are typically used to simulate fading. Many fading models have been developed over the last four decades, making use of several statistical distributions (Rice, Rayleigh, Nakagamim, etc.) and with different degrees of complexity. In this chapter, we describe some of the most important statistical models developed for the simulation of wireless fading channels, paying special attention to the accuracycomplexity tradeoff and discussing the application domain where each of them is more appropriate. Indeed, the main purpose of this chapter is providing clear algorithms for the efficient simulation of each of the channels described (which are often hard to find in the literature), rather than focusing only on the theoretical aspects (which are also covered). In order to achieve this purpose, several case studies are introduced throughout the chapter, showing how to simulate realworld channels (at < different degrees of detail and complexity) for practical applications. CRC Press9781482225495^Simulation Technologies in Networking and Communications: Selecting the Best Tool for the Test265EntidadLugarPginasReferencia/URLTipo de publicacinDAn Adaptive Population Importance Sampler: Learning from UncertaintyzMonte Carlo (MC) methods are wellknown computational techniques, widely used in different fields such as signal processing, communications and machine learning. An important class of MC methods is composed of importance sampling (IS) and its adaptive extensions, such as population Monte Carlo (PMC) and adaptive multiple IS (AMIS). In this work, we introduce a novel adaptive and iterated importance sampler using a population of proposal densities. The proposed algorithm, named adaptive population importance sampling (APIS), provides a global estimation of the variables of interest iteratively, making use of all the samples previously generated. APIS combines a sophisticated scheme to build the IS estimators (based on the deterministic mixture approach) with a simple temporal adaptation (based on epochs). In this way, APIS is able to keep all the advantages of both AMIS and PMC, while minimizing their drawbacks. Furthermore, APIS is easily parallelizable. The cloud of proposals is adapted in such a way that local features of the target density can be better taken into account compared to single global adaptation procedures. The result is a fast, simple, robust and highperformance algorithm applicable to a wide range of problems. Numerical results show the advantages of the proposed sampling scheme in four synthetic examples and a localization problem in a wireless sensor network.http://vixra.org/abs/1405.0280Informe Tcnico en viXra7Efficient Combination of Partial Monte Carlo EstimatorsIn many practical scenarios, including those dealing with large data sets, calculating global estimators of unknown variables of interest becomes unfeasible. A common solution is obtaining partial estimators and combining them to approximate the global one. In this technical report, we focus on minimum mean squared error (MMSE) estimators, introducing two efficient linear schemes for the fusion of partial estimators. The proposed approaches are valid for any type of partial estimators, although in the simulated scenarios we concentrate on the combination of Monte Carlo estimators due to the nature of the problem addressed. Numerical results show the good performance of the novel fusion methods with only a fraction of the cost of the asymptotically optimal solution.http://vixra.org/abs/1410.0035dExtremely Efficient AcceptanceRejection Method for Simulating Uncorrelated Nakagami Fading ChannelsVMultipath fading is one of the most common distortions in wireless communications. The simulation of a fading channel typically requires drawing samples from a Rayleigh, Rice or Nakagami distribution. The Nakagamim distribution is particularly important due to its good agreement with empirical channel measurements, as well as its ability to generalize the wellknown Rayleigh and Rice distributions. In this paper, a simple and extremely efficient rejection sampling (RS) algorithm for generating independent samples from a Nakagamim distribution is proposed. This RS approach is based on a novel hat function composed of three pieces of wellknown densities from which samples can be drawn easily and efficiently. The proposed method is valid for any combination of parameters of the Nakagami distribution, without any restriction in the domain and without requiring any adjustment from the final user. Simulations for several parameter combinations show that the proposed approach attains acceptance rates above 90% in all cases, outperforming all the RS techniques currently available in the literature.http://vixra.org/abs/1407.0133DThe FUSS algorithm: A Fast Universal Selftuned Sampler within GibbsGibbs sampling is a wellknown Markov Chain Monte Carlo (MCMC) technique, widely applied to draw samples from multivariate target distributions which appear often in many different fields (machine learning, finance, signal processing, etc.). The application of the Gibbs sampler requires being able to draw efficiently from the univariate fullconditional distributions. In this work, we present a simple, selftuned and extremely efficient MCMC algorithm that produces virtually independent samples from the target. The proposal density used is selftuned to the specific target but it is not adaptive. Instead, the proposal is adjusted during the initialization stage following a simple procedure. As a consequence, there is no ?fuss? about convergence or tuning, and the execution of the algorithm is remarkably sped up. Although it can be used as a standalone algorithm to sample from a generic univariate distribution, the proposed approach is particularly suited for its use within a Gibbs sampler, especially when sampling from spiky multimodal distributions. Hence, we call it FUSS (Fast Universal Selftuned Sampler). Numerical experiments on several synthetic and real data sets show its good performance in terms of speed and estimation accuracy.http://vixra.org/abs/1405.0263Nombre congresoTipo de participacinLugar del congreso RevisoresISBN o ISSNFecha inicio congresoFecha fin congresoTtulo de las actasLA measure of the overlapping of two densities: The JensenFisher divergenceoThe measure of Jensen?Fisher divergence between probability distributions is introduced and its theoretical grounds set up. This quantity, in contrast to the remaining Jensen divergences, grasps the fluctuations of the probability distributions because it is controlled by the (local) Fisher information, which is a gradient functional of the distribution. So it is appropriate and informative when studying the similarity of distributions, mainly for those having oscillatory character. The new Jensen?Fisher divergence shares with the Jensen?Shannon divergence the following properties: nonnegativity, additivity when applied to an arbitrary number of probability densities, symmetry under exchange of these densities, vanishing under certain conditions, and definiteness even when these densities present noncommon zeros. Moreover, the Jensen?Fisher divergence is shown to be expressed in terms of the relative Fisher information as the Jensen?Shannon divergence does in terms of the Kullback?Leibler or relative Shannon entropy. Finally, the usefulness of the JensenFisher divergence is illustrated in some particular examples.XInternational Symposium on Orthogonality, Quadrature and Related Topics (ORTHOQUAD 2014)960$Puerto de la Cruz, Tenerife, Espaa. 03770427
20/01/2014
24/01/2014ORTHOQUAD 2014)An Adaptive Population Importance SamplerhMonte Carlo (MC) methods are widely used in signal processing, machine learning and communications for statistical inference and stochastic optimization. A wellknown class of MC methods is composed of importance sampling and its adaptive extensions (e.g., population Monte Carlo). In this work, we introduce an adaptive importance sampler using a population of proposal densities. The novel algorithm provides a global estimation of the variables of interest iteratively, using all the samples generated. The cloud of proposals is adapted by learning from a subset of previously generated samples, in such a way that local features of the target density can be better taken into account compared to single global adaptation procedures. Numerical results show the advantages of the proposed sampling scheme in terms of mean absolute error and robustness to initialization.QIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)Florencia (Italia)978147992893410.1109/ICASSP.2014.6855166
04/05/2014
09/05/201480888092iProceedings of the 39th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),Building train schedules from frequency mapsThe railway planning process, due to its complexity, is commonly divided in a set of successiv<.e stages comprising network design, line planning, scheduling, timetabling, rolling stock and personnel scheduling. From a practical point of view, frequencies are line by line obtained following a regular double direction schema with constant headways. After this, a synchronization process is followed to improve connectivity among lines. In the past few years a set of acceleration strategies for managing these congestion problems have attracted increasing interest, mainly those based on controlling the frequency of vehicles at stops (e.g. the so called shortturning and deadheading approaches). Usually, the output of these models is an optimal frequency plan including new cycles and deadheading trips between various critical stations. After this stage, the frequency plan should be finally converted into a concrete and compatible train schedule containing departure and arrival vehicle times at stops. This process can be viewed as a location problem where each service is represented as segment to be located in a timespace diagram subject to certain sets of constraints. In this paper we resent general integer linear programming model in order to obtain such schedules for a given frequency distribution previously obtained and taking into account network capacity and safety constraints with the objective of preserving regularity as much as possible.<International Symposium on Locational Decision (ISOLDE 2014)Npoles, Italia.
20/06/2014
24/06/2014ISOLDE 2014]Circular sparse rulers based on coprime sampling for compressive power spectrum estimation Novedoso diseo de patrones de muestreo de seales digitales, que permite la reconstruccin de su potencia de espectro, utilizando tan slo un nmero muy reducido de muestras. :2014 IEEE Global Communications Conference (GLOBECOM 2014)Austin, Texas, Estados Unidos.978147993512310.1109/GLOCOM.2014.7037272
08/12/2014
12/12/201430443050*2014 IEEE Global Communications Conference#Autor: M. Elena Dominguez Jimenez//4Autor: Nuria Gonzlez Prelcic Universidade de Vigo//LGrouped sparsity algorithm for Multichannel Intracardiac ECG SynchronizationdIn this paper, a new method is presented to ensure automatic synchronization of intracardiac ECG data, yielding a threestage algorithm. We first compute a robust estimate of the derivative of the data to remove lowfrequency perturbations. Then we provide a groupedsparse representation of the data, by means of the Group LASSO, to ensure that all the electrical spikes are simultaneously detected. Finally, a postprocessing step, based on a variance analysis, is performed to discard false alarms. Preliminary results on real data for sinus rhythm and atrial fibrillation show the potential of this approach./European Signal Processing Conference (EUSIPCO)Lisboa (Portugal) 22195491
01/09/2014
05/09/201415371541GProceedings of the 22nd European Signal Processing Conference (EUSIPCO)9Independent Doubly Adaptive Rejection Metropolis SamplingsAdaptive Rejection Metropolis Sampling (ARMS) is a wellknown MCMC scheme for generating samples from onedimensional target distributions. ARMS is widely used within Gibbs sampling, where automatic and fast samplers are often needed to draw from univariate fullconditional densities. In this work, we propose an alternative adaptive algorithm (IA2RMS) that overcomes the main drawback of ARMS (an uncomplete adaptation of the proposal in some cases), speeding up the convergence of the chain to the target. Numerical results show that IA2RMS outperforms the standard ARMS, providing a correlation among samples close to zero.10.1109/ICASSP.2014.685515880488052(Monte Carlo Limit Cycle CharacterizationHThe fixed point implementation of IIR digital filters usually leads to the appearance of zeroinput limit cycles, which degrade the performance of the system. In this paper, we develop an efficient Monte Carlo algorithm to detect and characterize limit cycles in fixedpoint IIR digital filters. The proposed approach considers filters formulated in the state space and is valid for any fixed point representation and quantization function. Numerical simulations on several highorder filters, where an exhaustive search is unfeasible, show the effectiveness of the proposed approach.10.1109/ICASSP.2014.6855167804380472On the Darboux transformations for banded matricesThe Darboux transformations provide, joint with other applications, a method for obtaining solutions of some integrable systems. In this work, the concepts of Darboux factorization and Darboux transformations for arbitrary Hessenberg banded matrices are analyzed. Specifically, the existence of this kind of factorization is studied, and some sufficient conditions for the uniqueness are determinedHInternacional Symposium on Orthogonality and Quadrature (ORTHOQUAD 2014)1Universidad de La Laguna (Santa Cruz de Tenerife)
25/01/2014`On the use of Zero Padding with discrete cosine transform TypeII in multicarrier communicationsNuevo algoritmo que utiliza la Transformada discreta del Coseno, tipo II, para transmitir seales digitales extendidas con ceros.922nd European Signal Processing Conference (EUSIPCO 2014)Lisboa, Portugal.9780992862619825829=Proceedings of the 22nd European Signal Processing ConferenceCAutor: M. Elena Dominguez Jimenez//Autor: Gabriela Sansigre Vidal//3Autor: Fernando Cruz Roldan Universidad de Alcal//Orthogonal MCMC AlgorithmsMonte Carlo (MC) methods are widely used in signal processing, machine learning and stochastic optimization. A wellknown class of MC methods are Markov Chain Monte Carlo (MCMC) algorithms. In this work, we introduce a novel parallel interacting MCMC scheme, where the parallel chains share information using another MCMC technique working on the entire population of current states. These parallel ?vertical? chains are led by randomwalk proposals, whereas the ?horizontal? MCMC uses a independent proposal, which can be easily adapted by making use of all the generated samples. Numerical results show the advantages of the proposed sampling scheme in terms of mean absolute error, as well as robustness w.r.t. to initial values and parameter choice.4IEEE Workshop on Statistical Signal Processing (SSP)Gold Coast (Australia)978147994975510.1109/SSP.2014.6884651
29/06/2014
02/07/2014364367LProceedings of the 2014 IEEE Workshop on Statistical Signal Processing (SSP)9There is something about approximation beyond extremalitySe repasan varios resultados sobre interpolacin de funciones analticas en los que se extienden a polinomios interpoladores generales propiedades que hasta la fecha slo se haban probado para polinomios de tipo extremal ORTHOQUAD 2014Puerto de la Cruz, Tenerife10.1016/j.cam.2014.10.007155170,Proceedings of the OrthoQuad 2014 ConferenceComentarios Mrito:Revisin de artculos para Journal of Approximation TheoryRevisin de artculos&Autor: Maria Dolores Barrios Rolania//gRevisora de Proceedings of IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM 2014)rRevisora de artculo de investigacin para este relevante congreso internacional, organizado por el IEEE en 2014. FechaTipo+Autora de reseas para Mathematical ReviewsRevisin de trabajos2Responsabilidades en publicaciones internacionales]
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