S³: Time Frequency Array Signal Processing: Multi-Dimensional processing for non-stationary signals

Séminaire le 20 Mai 2016, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Adel Belouchrani

Conventional time-frequency analysis methods are being extended to data arrays, and there is a potential for a great synergistic development of new advanced tools by exploiting the joint properties of time-frequency methods and array signal processing methods. Conventional array signal processing assumes stationary signals and mainly employs the covariance matrix of the data array. This assumption is motivated by the crucial need in practice for estimating sample statistics by resorting to temporal averaging under the additional hypothesis of ergodic signals. When the frequency content of the measured signals is time varying (i.e., nonstationary signals), this class of approaches can still be applied. However, the achievable performances in this case are reduced with respect to those that would be achieved in a stationary environment. Instead of considering the nonstationarity as a shortcoming, Time Frequency Array Processing   takes advantage of the nonstationarity by considering it as a source of information in the design of efficient algorithms in such environments. This talk deals with this  relationship between time-frequency methods and array signal processing methods. Recent results on the performance analysis of the Time Frequency MUSIC algorithm will be also presented.

Bio: Adel Belouchrani was born in Algiers, Algeria, on May 5, 1967. He received the State Engineering degree in 1991 from Ecole Nationale Polytechnique (ENP), Algiers, Algeria, the M.S. degree in signal processing from the Institut National Polytechnique de Grenoble (INPG), France, in 1992, and the Ph.D. degree in signal and image processing from Télécom Paris (ENST), France, in 1995. He was a Visiting Scholar at the Electrical Engineering and Computer Sciences Department, University of California, Berkeley, from 1995 to 1996. He was with the Department of Electrical and Computer Engineering, Villanova University, Villanova, PA, as a Research Associate from 1996 to 1997. From 1998 to 2005, he has been with the Electrical Engineering Department of ENP as Associate Professor. He is currently and since 2006 Full Professor at ENP. His research interests are in statistical signal processing, (blind) array signal processing, time-frequency analysis and time-frequency array signal processing with applications in biomedical and telecommunications. Professor Adel Belouchrani is an IEEE Senior Member and has published over 180 technical publications including 48  journal papers, 4 book chapters and 4 patents that have been cited over 5400 times according Google Scholar  and  over 2000 time according to ISI Web Of Science. He has supervised over 19 PhD students. Professor Adel Belouchrani is currently Associated Editor of the IEEE Transactions on Signal Processing and Editorial board member of the Digital signal processing Journal (Ed. Elsevier).  He has been recently nominated  as a founding member of the Algerian Academy of Science  and Technology.

Control of Fuel Cell Hybrid Power Systems

Séminaire le 9 Mai 2016, 15h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Prof. Jian Chen, College of Control Science and Engineering, Zhejiang University, Hangzhou, China

with the environment and energy crisis worsening, fuel cells have shown significant potential as an alternative energy conversion device with high efficiency and low environmental impact. In particular, Fuel cells are promising for new energy automotive applications. Fuel cell hybrid power systems usually include fuel cells and lithium-Ion batteries. In this presentation, I will talk about control of fuel cell systems, SOC Estimation of Lithium-Ion Batteries, and adaptive control strategies of fuel cell/battery hybrid power systems.

Biography: Jian Chen (M’06-SM’10) received the B.E. and M.E. degrees from Zhejiang University, Hangzhou, China, in 1998 and 2001, respectively, and the Ph.D. degree from Clemson University, South Carolina, USA, in 2005. From 2006 to 2008, he was as a research fellow working on fuel cell modeling and ­control at the University of Michigan, Ann Arbor, MI, USA. He joined IdaTech LLC, Oregen, USA, working on fuel cell back power systems and Proterra Inc., South Carolina, USA, working on the National Fuel Cell Bus Program, in 2008 and 2012, respectively. In 2013, he joined the Department of Control Science and Engineering, Zhejiang University, Hangzhou, China. Dr. Chen is currently a professor with the College of Control Science and Engineering, Zhejiang University, Hangzhou, China. He has been supported by the Chinese Recruitment Program of Global Youth Experts since 2012 and received the Major Program of National Natural Science Foundation of China on Modeling and Control of Fuel Cell vehicles in 2014. His research interests include fuel cell modeling and control, battery management, visual servo techniques, and nonlinear control.

Séminaire d'Automatique du Plateau de Saclay: Virtual Inertia Emulation and Placement in Power Grids

Séminaire le 15 Avril 2016, 11h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Florian Dörfler (ETH Zurich)

A major transition in the operation of electric power grids is the replacement of bulk generation based on synchronous machines by distributed generation based on low-inertia power electronic sources. The accompanying "loss of rotational inertia" and the fluctuations by renewable sources jeopardize the system stability, as testified by the ever-growing number of frequency incidents. As a remedy, numerous studies demonstrate how virtual inertia can be emulated through various devices, but few of them address the question of "where" to place this inertia. It is however strongly believed that the placement of virtual inertia hugely impacts system efficiency, as demonstrated by recent case studies. We carry out a comprehensive analysis in an attempt to address the optimal inertia placement problem, considering a linear network-reduced power system model along with an H2 performance metric accounting for the network coherency. The optimal inertia placement problem turns out to be non-convex, yet we provide a set of closed-form global optimality results for particular problem instances as well as a computational approach resulting in locally optimal solutions. We illustrate our results with a three-region power grid case study and compare our locally optimal solution with different placement heuristics in terms of different performance metrics.

Séminaire d'Automatique du Plateau de Saclay: A modular design of incremental Lyapunov functions for microgrid control

Séminaire le 15 Avril 2016, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Claudio De Persis (Groningen University)

In this talk we propose a Lyapunov based analysis of microgrids. The starting point is an energy function comprising the kinetic energy associated with the elements that emulate the rotating machinery and terms taking into account the reactive power stored in the lines and dissipated on shunt elements. We then shape this energy function with the addition of an adjustable voltage-dependent term, and construct incremental storage functions satisfying suitable dissipation inequalities. The choice of the voltage-dependent term depends on the voltage dynamics/controller under investigation. Several microgrids dynamics that have similarities or coincide with dynamics already considered in the literature are captured in this incremental energy analysis framework. These incremental storage functions allow for a complete analysis of the coupled microgrid obviating the need for simplifying linearization techniques and for the restrictive decoupling assumption in which the frequency dynamics is fully separated from the voltage one.

Improved Millimeter-Wave Radar Concealed-Threat Person Scanning

Séminaire le 8 Avril 2016, 14h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Carey M. Rappapor

Metal-detecting airport security scanners for airline passengers are being replaced by millimeter-wave imagers. These new systems are much better at revealing concealed manmade objects, but they can be improved. At our Advanced Imaging Technology Lab at Northeastern University in Boston, we are developing a custom-designed elliptical toroid reflector antenna which allows multiple overlapping beams for focused wide-angle illumination to speed data acquisition and accurately image strongly inclined body surfaces.  We have developed the concept of the Blade Beam Reflector both as a single transmitting antenna and a multi-beam Toroidal Reflector, with multiple feeds. Each feed generates a different incident beam with different viewing angles, while still maintaining the blade beam configuration of narrow slit illumination in the vertical direction.  Having multiple transmitters provides horizontal resolution and imaging of full 120 deg. of body.  Furthermore, the reflector can simultaneously be used for receiving the scattered field, with high gain, overlapping, high vertical resolution beams for each transmitting or receiving array element. The multistatic transmitting and receiving array configuration sensing avoids dihedral artifacts from body crevices and reduces non-specular drop-outs, and will leads to a faster, higher resolution, and less expensive security system.

Bio — Carey M. Rappaport received five degrees from the Massachusetts Institute of Technology:  the SB in Mathematics, the SB, SM, and EE in Electrical Engineering in June 1982, and the PhD in Electrical Engineering in June 1987.  He is married to Ann W. Morgenthaler, and has two children, Sarah and Brian. Prof. Rappaport joined the faculty at Northeastern University in Boston, MA in 1987.  He has been Professor of Electrical and Computer Engineering since July 2000. In 2011, he was appointed College of Engineering Distinguished Professor.  He was Principal Investigator of an ARO-sponsored Multidisciplinary University Research Initiative on Humanitarian Demining, Co-Principal Investigator of the NSF-sponsored Engineering Research Center for Subsurface Sensing and Imaging Systems (CenSSIS), and Co-Principal Investigator and Deputy Director of the DHS-sponsored Awareness and Localization of Explosive Related Threats (ALERT) Center of Excellence. Prof. Rappaport has authored over 400 technical journal and conference papers in the areas of microwave antenna design, electromagnetic wave propagation and scattering computation, and bioelectromagnetics, and has received two reflector antenna patents, two biomedical device patents and three subsurface sensing device patents.  He was awarded the IEEE Antenna and Propagation Society's H.A. Wheeler Award for best applications paper, as a student in 1986.  He is a member of Sigma Xi and Eta Kappa Nu professional honorary societies.

S³: Topological Pattern Selection in Recurrent Networks

Séminaire le 1 Avril 2016, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Alireza Bahraini

One of the differences between memory function of hypocampus and  neural networks situated at neocortex is that in the  latter memory operation still reflect the topography informing synaptic connections. This means that the activity of a unit relates also to its position in the tissue.
We introduce two approaches for incorporating the information of the geometry  of the underlying neural network into its dynamics. This phenomenon is carried out based on two probability rules for selecting storing patterns. First  a Gibbs type distribution inspired by the architecture of the network is applied. We are then led to a second method to introduce topological effects on the dynamics of the network. In both approaches a significant enhancement on the capacity of the network is observed after considerable rigorous computations.

Some References:
1- Bahraini,A, .  Abbassian,A.  Topological Pattern Selection in Recurrent Networks, Journal of Neural Networks, 31, 2012, 22-32.
2- Roudi, Y, Treves, A,. An associative Network with Spatially Organized Connectivity,2004, Journal of Statistical Mechanics.
3- Gallan, R., F., On how network architecture determines the dominant patterns of spontaneous neural activity, PLoS One , 2008.

Bio: I obtained my DEA in 2001 and my PhD in 2004 at University Paris 7 under the supervision of Professor Daniel Bennequin. The title of my thesis was Super-symmetry and Complex Geometry. I joined the department of mathematical sciences of Sharif university of technology as an assistant
professor in 2004 and in 2012 I became an associate professor at the same department.

S³: Solving large-scale inverse problems using forward-backward based methods

Séminaire le 11 Mars 2016, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Audrey Repett: post-doctoral researcher at the Heriot-Watt university, in Scotland

Recent developments in imaging and data analysis techniques came along with an increasing need for fast convex optimization methods for solving large scale problems.  A simple optimization strategy to minimize the sum of a Lipschitz differentiable function and a non smooth function is the forward-backward algorithm. In this presentation, several approaches to accelerate convergence speed and to reduce complexity of this algorithm will be proposed. More precisely, in a first part, preconditioning methods adapted to non convex minimization problems will be presented, and in a second part, stochastic optimization techniques will be described in the context of convex optimization. The different proposed methods will be used to solve several inverse problems in signal and image processing.

Bio: Audrey Repetti is a post-doctoral researcher at the Heriot-Watt university, in Scotland. She received her M.Sc. degree from the Université Pierre et Marie Curie (Paris VI) in applied mathematics, and her Ph.D. degree from the Université Paris-Est Marne-la-Vallée in signal and image processing. Her research interests include convex and non convex optimization, and signal and image processing.

S³: Data-driven, Interactive Scientific Articles in a Collaborative Environment with Authorea

Séminaire le 4 Mars 2016, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Nathan Jenkins

Most tools that scientists use for the preparation of scholarly manuscripts, such as Microsoft Word and LaTeX, function offline and do not account for the born-digital nature of research objects. Also, most authoring tools in use today are not designed for collaboration and as scientific collaborations grow in size, research transparency and the attribution of scholarly credit are at stake. In this talk, I will show how Authorea allows scientists to collaboratively write rich data-driven manuscripts on the web–articles that would natively offer readers a dynamic, interactive experience with an article’s full text, images, data, and code–paving the road to increased data sharing, data reuse, research reproducibility, and Open Science.

Bio: Nathan Jenkins is co-founder and CTO of Authorea.  A condensed matter physicist, Nathan completed his Ph.D. at the University of Geneva where he studied electronic properties of high temperature superconductors at the atomic scale. He was then awarded a Swiss National Science Foundation scholarship to study as a postdoc at NYU where examined the dynamics of protein folding via atomic force microscopy.  Hailing from California, Nathan resides between Geneva, Switzerland and New York City.

S³: Robust Factor Analysis of Time Series with Long-Memory and Outliers: Application to Air Pollution data

Séminaire le 19 Février 2016, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Valderio Anselmo Reisen

This paper considers the factor modeling for high-dimensional time series with short and long-memory properties and in the presence of additive outliers. For this, the factor model studied by Lam and Yao (2012) is extended to consider the presence of additive outliers. The estimators of the number of factors are obtained by an eigenanalysis of a non-negative definite matrix, i.e., the covariance matrix or the robust covariance matrix. The proposed methodology is analyzed in terms of the convergence rate of the number factors by means of Monte Carlo simulations. As an example of application, the robust factor analysis is utilized to identify pollution behavior for the pollutant PM10 in the Greater Vitoria region ( ES, Brazil) aiming to reduce the dimensionality of the data and for forecasting investigation.

Bio: Valderio Anselmo Reisen is full Professor of Statistics at the Federal University of Espirito Santo (UFES), Vitoria, Brazil. His main interests are time series analysis, forecasting, econometric modeling, bootstrap, robustness in time series, unit root processes, counting processes,  environmental and economic data analysis, periodically correlated processes, and multivariate time series.


S³: Robust spectral estimators for long-memory processes: Time and frequency domain approaches.

Séminaire le 29 Janvier 2016, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Valderio Anselmo Reisen

This paper discusses the outlier effects on the estimation of a spectral estimator for long memory process under additive outliers and proposes robust spectral estimators. Some asymptotic properties of the proposed robust methods are derived and Monte Carlo simulations investigate their empirical properties.  Pollution series, such as, PM (Particulate matter), SO2 (Sulfur dioxide), are the applied examples investigated here to show the usefulness of the proposed  robust methods in real applications.  These pollutants present, in general, observations with high levels of pollutant concentrations which may produce sample densities with heavy tails  and these high levels of concentrations can be identified as outliers which can destroy the statistical properties of sample functions such as the standard mean,  covariance and the periodogram.

Bio: Valderio Anselmo Reisen is full Professor of Statistics at the Federal University of Espirito Santo (UFES), Vitoria, Brazil. His main interests are time series analysis, forecasting, econometric modeling, bootstrap, robustness in time series, unit root processes, counting processes,  environmental and economic data analysis, periodically correlated processes, and multivariate time series.

Séminaire S³

S³ seminar: A Two-Round Interactive Receiver Cooperation Scheme for Multicast Channels

Séminaire le 8 Janvier 2016, 16h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Victor Exposito

We consider the problem of transmitting a common message from a transmitter to two receivers over a broadcast channel, which is also called multicast channel in this case. The two receivers are allowed to cooperate with each other in full-duplex over non-orthogonal channels. We investigate the information-theoretic upper and lower bounds on the achievable rate of such channels. In particular, we propose a two-round cooperation scheme in which the receivers interactively perform compress-forward (CF) and then decode-forward (DF) to improve the achievable rate. Numerical results comparing the proposed scheme to existing schemes and the cutset upper bound are provided. We show that the proposed scheme outperforms the non-interactive DF and CF schemes as well as the noisy network coding. The gain over the DF scheme becomes larger when the channel becomes symmetric, while the gain over the CF scheme becomes larger when the channel becomes asymmetric.
Bio: Victor Exposito received the Engineering and M.Sc. degree (valedictorian) in communication systems and networks from the Institut National des Sciences Appliquées de Rennes (INSA-Rennes), Rennes, France, in 2014. He is currently working at Mitsubishi Electric R&D Centre Europe (MERCE-France), Rennes, France and Ecole Supérieure d’Electricité (CentraleSupélec), Gif-sur-Yvette, France, toward the Ph.D. degree. His current research interests mainly lie in the area of network information theory.

Characterization of Photovoltaic systems for Large Scale Solar Power Generation

Séminaire le 17 Décembre 2015, 16h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Fernando Mancilla-David

Photovoltaic electric power generation is increasingly attracting the attention of industry and academia mainly motivated by the urgent need to depart from fossil fuel-based electricity generation. As the cost of PV panels production continues to decrease, it is expected that bulk solar power generation will be competitive with other forms of renewable energy, and hence massively deployed. Grid-connected PV power plants are currently generating up to a few megawatts as a single unit, and built through PV arrays containing hundreds of thousands of solar cells. The PV plant is connected to the ac grid via a power electronics-based interphase realized through a voltage source inverter.

The seminar presents research conducted at the University of Colorado Denver on the modeling and control of this type of systems, often referred to as large PV power plants. The modeling of the various elements making up a large PV power plant, namely PV cells, inverter and an equivalent of the ac grid, will be discussed. Furthermore, the seminar addresses the PV array's maximum power point tracking and the regulation of current injection into the ac grid. Considerations regarding the identification of solar irradiance are also to be discussed. The modeling and control techniques presented within the seminar are validated through computer simulations and/or experimentation performed in the University of Colorado Denver campus.


Fernando Mancilla-David is an Associate Professor at the University of Colorado Denver, where he teaches and directs research in energy and power systems as a faculty member of the Electrical Engineering Department. Prof. Mancilla-David received the B.S. degree in electrical engineering from the Universidad Tecnica Federico Santa Maria, Valparaiso, Chile, in 1999, and the M.S. and Ph.D. degrees in electrical engineering from the University of Wisconsin-Madison, Madison, Wisconsin, United State of America, in 2002 and 2007, respectively. He has been a visiting professor in several universities in Europe and has coauthored more than 60 technical articles, mostly in the area of utility applications of power electronics.

S³: Gegenbauer polynomials and positive definiteness

Séminaire le 27 Novembre 2015, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Christian Berg, University of Copenhagen, Denmark

Abstract file

Bio: Professor Christian Berg graduated from Næstved Gymnasium 1963 and studied mathematics at the University of Copenhagen. He became cand.scient. in 1968, lic.scient. (ph.d.) in 1971, and dr. phil. in 1976. Christian Berg received the gold medal of the University of Copenhagen in 1969 for a paper about Potential Theory.
He became assistant professor at University of Copenhagen in 1971, associated professor in 1972 and professor since 1978. Christian Berg had several research visits abroad, in USA, France, Spain, Sweden and Poland.
He became member of The Royal Danish Academy of Sciences and Letters 1982, vice-president 1999-2005. Member of The Danish Natural Sciences Research Council 1985-1992. President of the Danish Mathematical Society 1994-98. Member of the editorial board of Journal of Theoretical Probability (1988-1999) and Expositiones Mathematicae since 1993. Member of the advisory board of Arab Journal of Mathematical Sciences since 1995.
At the Department of Mathematics of the University of Copenhagen, he was Member of the Study Board 1972-74, member of the Board 1977-1984, 1993-1995, chairman 1996-97, and Director of the Institute for Mathematical Sciences 1997-2002.
Christian Berg  has so far published app. 110 scientific papers in international journals, mainly about potential theory, harmonic analysis and moment problems.

S³:Bayesian Fusion of Multiple Images - Beyond Pansharpening

Séminaire le 13 Novembre 2015, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Jean-Yves Tourneret, University of Toulouse, FR

This presentation will discuss new methods for fusing high spectral resolution images (such as hyperspectral images) and high spatial resolution images (such as panchromatic images) in order to provide images with improved spectral and spatial resolutions. These methods are based on Bayesian estimators exploiting prior information about the target image to be recovered, constructed by interpolation or by using dictionary learning techniques. Different implementations based on MCMC methods, optimization strategies or on the resolution of Sylvester equations will be explored

Bio: Jean-Yves TOURNERET (SM08) received the ingenieur degree in electrical engineering from the Ecole Nationale Supérieure d'Electronique, d'Electrotechnique, d'Informatique, d'Hydraulique et des Télécommunications (ENSEEIHT) de Toulouse in 1989 and the Ph.D. degree from the National Polytechnic Institute from Toulouse in 1992. He is currently a professor in the university of Toulouse (ENSEEIHT) and a member of the IRIT laboratory (UMR 5505 of the CNRS). His research activities are centered around statistical signal and image processing with a particular interest to Bayesian and Markov chain Monte Carlo (MCMC) methods. He has been involved in the organization of several conferences including the European conference on signal processing EUSIPCO'02 (program chair), the international conference ICASSP'06 (plenaries), the statistical signal processing workshop SSP'12 (international liaisons), the International Workshop on Computational Advances in Multi-Sensor Adaptive Processing CAMSAP 2013 (local arrangements), the statistical signal processing workshop SSP'2014 (special sessions), the workshop on machine learning for signal processing MLSP'2014 (special sessions). He has been the general chair of the CIMI workshop on optimization and statistics in image processing hold in Toulouse in 2013 (with F. Malgouyres and D. Kouamé) and of the International Workshop on Computational Advances in Multi-Sensor Adaptive Processing CAMSAP 2015 (with P. Djuric). He has been a member of different technical committees including the Signal Processing Theory and Methods (SPTM) committee of the IEEE Signal Processing Society (2001-2007, 2010-present). He has been serving as an associate editor for the IEEE Transactions on Signal Processing (2008-2011, 2015-present) and for the EURASIP journal on Signal Processing (2013-present).

Access information are available on the website http://www.lss.supelec.fr/scube/

S³: Algorithmes d’Estimation et de Détection en contexte Hétérogène Rang Faible

Séminaire le 6 Novembre 2015, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
A. Breloy, Ecole Normale Supérieure de Cachan, FR

Covariance Matrix (CM) estimation is an ubiquitous problem in statistical signal processing. In terms of application purposes, the accuracy of the CM estimate directly impacts the performance of the considered adaptive process. In the context of modern data-sets, two major problems are currently at stake:

- Samples are often drawn from heterogeneous (non gaussian) distributions.
- Only a low sample support is available.

To respond to these problems, one has to develop new estimation tools that are based on an appropriate modeling of the data.

Bio: Arnaud Breloy graduated from Ecole Centrale Marseille and recived a Master's degree of Signal and Image Processing from university of Aix-Marseille in 2012-13. Formerly Ph.D student at the SATIE and SONDRA laboratories, he is currently lecturer at University Institute of Technology of Ville d’Avray. His research interests focuses on statistical signal processing, array and radar signal processing, robust estimation methods and low rank methods.

Mismatched decoding

Séminaire le 22 Octobre 2015, 11h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Dr. Guillen i Fabregas

This talk will review the mismatched decoding problem. In particular, the talk will review the fundamental limits of mismatched channel-decoder pairs in a point-to-point setup, with particular focus on random coding ensembles, achievable information rates and the corresponding error exponents.

Albert Guillén i Fàbregas was born in Barcelona in 1974. In 1999 he received the Telecommunication Engineering Degree and the Electronics Engineering Degree from Universitat Politècnica de Catalunya and Politecnico di Torino, respectively, and the Ph.D. in Communication Systems from Ecole Polytechnique Fédérale de Lausanne (EPFL) in 2004.
Since 2011 he has been a Research Professor of the Institució Catalana de Recerca i Estudis Avançats (ICREA) at the Department of Information and Communication Technologies,
Universitat Pompeu Fabra. He is also an Adjunct Researcher at the Department of Engineering, University of Cambridge, where he was a Reader and a Fellow of Trinity Hall. He has held appoinments at the New Jersey Institute of Technology, Telecom Italia, European Space Agency (ESA), Institut Eurecom, University of South Australia, as well as visiting appointments at TelecomParisTech (Paris), Universitat Pompeu Fabra, University of South Australia, Centrum Wiskunde & Informatica and Texas A&M University in Qatar. His research interests are in information theory, coding theory and communication theory. Dr. Guillén i Fàbregas received the Starting Grant from the European Research Council, the Young Authors Award of the 2004 European Signal Processing Conference, the 2004 Best Doctoral Thesis Award from the Spanish Institution of Telecommunications Engineers, and a Research Fellowship of the Spanish Government to join ESA. He is an Associate Editor of the IEEE Transactions on Information Theory and of the Foundations and Trends in Communications and Information Theory, Now Publishers. He is also a Senior Member of IEEE,  a member of theYoung Academy of Europe and was an Editor of the IEEE Transactions on Wireless Communications (2007-2011).

Pseudorational transfer functions and their spectral properties - an introductory survey

Séminaire le 15 Octobre 2015, 14h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Yutaka Yamamoto, univ of Kyoto

This talk gives an overview of the class of pseudorational transfer functions. This class consists of the ratio of entire functions of exponential type that are Laplace transforms of distributions with compact support. It gives rise to a convenient platform for dealing with distributed parameter systems whose state space is determined by bounded-time data.  Delay-differential systems, with retarded, neutral or distributed delays, are typical examples. We explore its interesting interplay with the ring of entire functions, and highlight some appealing structures as follows: Starting from a completely general input/output framework, we derive a concrete realization procedure based on the above fractional representation of transfer functions (or impulse responses).  It is then also possible to give a complete characterization of spectral properties of such realizations via zeros of the denominator of transfer functions.
Such spectral properties allow us to give a stability criterion and also an appropriate relationship between internal and external stability notions. Based on a concrete representation of the state space, we are led to a concrete characterization of left-shift invariant subspaces of H^2.  This result has a direct consequence on H-infinity control theory.
We also give a concise yet comprehensive and unified overview of such results.  The talk is concluded with this and also a criterion on the existence of a Bezout identity in this class.

Fronthaul Compression for Cloud Radio Access Networks: An Information Theoretic View

Séminaire le 28 Septembre 2015, 14h00 à CentraleSupelec (Gif-sur-Yvette) Amphi F3-09
Prof. Shlomo Shamai, EE Department, Technion-Israel Institute of Technology

Cloud radio access networks (C-RANs) emerge as appealing architectures for next-generation wireless/cellular systems whereby the processing/decoding is migrated from the local base-stations/radio units (RU) to a control/central units (CU) in the *cloud*. This is facilitated by fronthaul links connecting the RUs to the managing CUs. We focus on oblivious processing at the RU, and hence the fronthaul links carry digital information about the baseband signals, in the uplink from the RUs to the CU and vice versa in the downlink. The high data rate service demands in C-RANs, imply that even with fast (optical) front hauls, let alone for heterogeneous fronhauls, efficient compression of the basedand signals is essential. In this talk we focus on advanced robust signal processing solutions, emerging by network information theoretic concepts, and review also the basic approaches to this cloud network. Multi-hop fronthaul topologies are also discussed. Analysis and numerical results illustrate the considerable performance gains to be expected for different cellular models. Some interesting theoretical directions conclude the presentation.

S³: Bayesian Tomography

Séminaire le 25 Septembre 2015, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
John Skilling, Maximum Entropy Data Consultants Ltd, UK

Abstract: Click here

Bio: John Skilling was awarded his PhD in radio astronomy in 1969.  Through the 1970s and 1980s he was a lecturer in applied mathematics at Cambridge University, specialising in data analysis.  He left to concentrate on consultancy work, originally using maximum entropy methods but moving to Bayesian methodology when algorithms became sufficiently powerful.  John has been a prominent contributor to the “MaxEnt” conferences since their beginning in 1981.  He is the discoverer of the nested sampling algorithm which performs integration over spaces of arbitrary dimension, which is the basic operation dictated by the sum rule of Bayesian calculus.

S³: Is the Gaussian distribution "Normal"? Signal processing with alpha-stable distributions

Séminaire le 18 Septembre 2015, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Ecran E. Kuruoglu, Istituto di Scienza e Tecnologie dell'Informazione, Italy

There are solid reasons for the popularity of Gaussian models. They are easy to deal with, lead to linear equations, and they have a strong theoretical justification given by the Central Limit theorem. However, many data, manmade or natural, exhibit characteristics too impulsive or skewed to be successfully accommodated by the Gaussian model. The wide spread power laws in the nature, in internet, in linguistics, biology are very well known. In this talk we will challengethe "Normality" of the Gaussian distribution and will discuss the alpha‐stable distribution family which satisfies the generalised Central Limit Theorem. Alpha‐Stable distributions have received wide interest in the signal processing community and became state of the art models for impulsive noise and internet traffic in the last 20 years since the influential paper of Nikias and Shao in 1993. We will provide the fundamental theory and discuss the rich class of statistics this family enables us to work with including fractional order statistics, log statistics and extreme value statistics. We will present some application areas where alpha‐stable distributions had important success such as internet traffic modelling, SAR imaging, computational biology, astronomy, etc. We will also present recent research results on generalisation of source separation algorithms by maximizing non-alpha stability and also multivariate analysis using alpha-stable Bayesian networks. We will identify open problems which we hope will lead to fruitful discussion on further research on this family of distributions.

Bio: Ercan E. Kuruoglu was born in Ankara, Turkey in 1969. He obtained his BSc and MSc degrees both in Electrical and Electronics  Engineering  at  Bilkent  University  in  1991  and  1993  and  the  MPhil  and  PhD  degrees  in  Information  Engineering  at  the Cambridge University, in the Signal Processing Laboratory, in 1995 and 1998 respectively. Upon graduation from Cambridge, he joined the Xerox Research Center in Cambridge as a permanent member of theCollaborative Multimedia Systems Group. In 2000, he was in INRIA‐Sophia Antipolis as an ERCIM fellow. In 2002, he joined ISTI‐CNR, Pisa as a permanent member. Since 2006, he  is  an Associate Professor  and  Senior Researcher. He was  a  visiting professor  in Georgia Institute of Technology graduate  program  in  Shanghai  in  2007  and  2011. He was a 111 Project (Bringing Foreign Experts to China Program) Fellow and was a frequent visitor to Shanghai Jiao Tong University, China (2007‐2011). He was an Visiting Professor in Hong Kong, in August 2012 as a guest of the HK IEEE Chapter. He is a recipient of the Alexander von Humboldt Foundation Fellowship (2012‐2014) which allowed him to work in as a visiting scientist at Max‐Planck Institute for Molecular Biology. He was an Associate Editor for IEEE Transactions on Signal Processing in 2002‐2006 and for IEEE Transactions on Image Processing in 2005‐2009. He is currently the Editor in Chief of Digital Signal Processing: a Review Journal and also is in the editorial board of EURASIP Journal on Advances in Signal Processing. He was the Technical co‐Chair for EUSIPCO 2006, special sessions chair of EUSIPCO 2005 and tutorials  co‐chair of ICASSP 2014. He served  as  an  elected member of the IEEE  Technical Committee on  Signal Processing Theory and Methods (2004‐2010), was a member of IEEE Ethics committee in 2012 and is a Senior Member of IEEE. He was a plenary speaker at Data Analysis for Cosmology (DAC 2007) and ISSPA 2010 and tutorial speaker at ICSPCC 2012 and Bioinformatiha 2013 and 2014 . He is the author of more than 100 peer reviewed publications and holds 5 US, European and Japanese patents. His research interests  are  in  statistical  signal  processing  and  information  and  coding  theory  with  applications  in  image  processing, computational biology, telecommunications, astronomy and geophysics.


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