In a feedback system, besides the stabilization, the controllers are often designed to meet some performance specifications defined by H∞ norm minimization of corresponding sensitivity functions. From the practical point of view, if it is possible, it is desired the controller to be designed is stable. In this work, stable controller design to minimize the H∞ norm of the corresponding sensitivity function in a feedback system with a single-input single-output biproper infinite-dimensional real plant is considered. The plant may have infinitely many poles and simple zeros in the right-half-plane, however, its zeros are assumed to satisfy some growth condition. Interpolation-based approach will be used to design such a controller and a numerical example will be presented.

### Séminaire d'Automatique du Plateau de Saclay : Robust perfomance by a stable controller for infinite-dimensional plants

**Hakki Ulas Unal (Anadolu University)**

### Séminaire d'Automatique du Plateau de Saclay :On Control Lyapunov-Krasovskii Functionals and Stabilization in the Sample-and-Hold Sense of Nonlinear Time-Delay Systems

**Pierdomenico Pepe (Università degli Studi dell'Aquila)**

This talk deals with the stabilization in the sample-and-hold sense of nonlinear systems described by retarded functional differential equations. The notion of stabilization in the sample-and-hold sense has been introduced in 1997 by Clarke, Ledyaev, Sontag and Subbotin, for nonlinear delay-free systems. Roughly speaking, a state feedback (continuous or not) is said to be a stabilizer in the sample-and-hold sense if, for any given large ball and small ball of the origin, there exists a suitable small sampling period such that the feedback control law obtained by sampling and holding the above state feedback, with the given sampling period, keeps uniformly bounded all the trajectories starting in any point of the large ball and, moreover, drives all such trajectories into the small ball, uniformly in a maximum finite time, keeping them in, thereafter. In this talk suitable control Lyapunov-Krasovski functionals will be introduced and suitable induced state feedbacks (continuous or not), and it will be shown that these state feedbacks are stabilizers in the sample-and- hold sense, for fully nonlinear time-delay systems. Moreover, in the case of time-delay systems, implementation by means of digital devices often requires some further approximation due to non availability in the buffer of the value of the system variables at some past times, as it can be frequently required by the proposed state feedback. In order to cope with this problem, well known approximation schemes based on first order splines are used. It is shown, for fully nonlinear retarded systems, that, by sampling at suitable high frequency the system (finite dimensional) variable, stabilization in the sample-and-hold sense is still guaranteed, when the holden input is obtained as a feedback of the (first order) spline approximation of the (infinite dimensional) system state, whose entries are available at sampling times, and the state feedback is Lipschitz on any bounded subset of the Banach state space

### Séminaire d'Automatique du Plateau de Saclay : Optimal control and Lyapunov functions applied to the satellite attitude control

**Nadjim Horri (Coventry University)**

The use of Lyapunov functions is generally limited to proving the stability of a system with a given control law. In this presentation, Lyapunov functions are used to formulate optimal control problems as pointwise nonlinear programmes. These optimisation problems are equivalent to inverse optimal control problems. This approach is applied to satellite attitude control. The optimal attitude control problems under consideration will be the minimisation of the norm of the control torque subject to constraints on the convergence rate of a Lyapunov function. This approach improves the tradeoff between rapidity and energy consumption compared to a benchmark controller, which is taken to be a PD type controller without loss of generality. The phase space trajectories show that the solutions to some fundamental open loop optimization problems are particular cases of optimal control problem formulations based on the convergence rates of Lyapunov functions. This is the case of the minimum time single axis attitude control problem, which is a special case of the problem of maximizing the convergence rate of a Lyapunov function under maximum torque limitations. It is also the case of the problem of minimising toque for fixed manoeuvre time. The solution to this problem is a particular case of the problem of minimizing the norm of the control torque under a Lyapunov convergence rate constraint.

### S³: Condition monitoring using vibration signals

**Asoke K. Nandi**

Condition monitoring of machines is an essential part of smooth, efficient, safe, and productive operation of machines. In this presentation, focus will be on rotating machines and in the use of vibration signals. Classification of vibration signals to different states of machines has been achieved through the developments and applications of signal processing and machine learning. This presentation will cover research efforts and some case studies carried out over many years.

Bio: Professor Asoke K. Nandi received the degree of Ph.D. in Physics from the University of Cambridge, Cambridge (UK). He held academic positions in several universities, including Oxford (UK), Imperial College London (UK), Strathclyde (UK), and Liverpool (UK) as well as Finland Distinguished Professorship in Jyvaskyla (Finland). In 2013 he moved to Brunel University London (UK), to become the Chair and Head of Electronic and Computer Engineering. Professor Nandi is a Distinguished Visiting Professor at Tongji University (China) and an Adjunct Professor at University of Calgary (Canada).

In 1983 Professor Nandi contributed to the discovery of the three fundamental particles known as W+, W− and Z0 (by the UA1 team at CERN), providing the evidence for the unification of the electromagnetic and weak forces, which was recognized by the Nobel Committee for Physics in 1984. His current research interests lie in the areas of signal processing and machine learning, with applications to communications, gene expression data, functional magnetic resonance data, and biomedical data. He has made many fundamental theoretical and algorithmic contributions to many aspects of signal processing and machine learning. He has much expertise in “Big Data”, dealing with heterogeneous data, and extracting information from multiple datasets obtained in different laboratories and different times. He has authored over 500 technical publications, including 200 journal papers as well as four books, entitled Automatic Modulation Classification: Principles, Algorithms and Applications (Wiley, 2015), Integrative Cluster Analysis in Bioinformatics (Wiley, 2015), Automatic Modulation Recognition of Communications Signals (Springer, 1996), and Blind Estimation Using Higher-Order Statistics (Springer, 1999),. Recently he published in Blood, BMC Bioinformatics, IEEE TWC, NeuroImage, PLOS ONE, Royal Society Interface, and Signal Processing. The h-index of his publications is 63 (Google Scholar).

Professor Nandi is a Fellow of the Royal Academy of Engineering and also a Fellow of seven other institutions including the IEEE and the IET. Among the many awards he received are the Institute of Electrical and Electronics Engineers (USA) Heinrich Hertz Award in 2012, the Glory of Bengal Award for his outstanding achievements in scientific research in 2010, the Water Arbitration Prize of the Institution of Mechanical Engineers (UK) in 1999, and the Mountbatten Premium, Division Award of the Electronics and Communications Division, of the Institution of Electrical Engineers (UK) in 1998.

### Séminaire d'Automatique du Plateau de Saclay : Inverse optimal control: the sub-Riemannian case

**Frédéric Jean (ENSTA)**

An inverse control problem is formulated as follows: given a set of trajectories and a control system, find a cost such that these paths are optimal. The first question to ask is the uniqueness of the solution of such a problem. For general classes of costs the problem appears to be very difficult, even with a trivial dynamics. We are therefore interested in this issue for the class of costs which are quadratic in the control, when the dynamics depend linearly in the control (Riemannian and sub-Riemannian case). In this case we can reduce the problem to the question of the existence of geodesically equivalent metrics and the existing results will be described, from the theorem of Levi-Civita (1890) to those we obtained recently with Sofya Maslovskaya and Igor Zelenko.

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

**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

**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

**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

**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

**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

**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

**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

**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

**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.

**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.

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Séminaire S³

www.lss.supelec.fr/scube/

seminaire.scube@l2s.centralesupelec.fr

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

**Victor Exposito**

**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

**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.

Biography

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

**Christian Berg, University of Copenhagen, Denmark**

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

**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

**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.

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