Sub-Nyquist Sampling: Bridging Theory and Practice

Sampling theory encompasses all aspects related to the conversion of continuous-time signals to discrete streams of numbers. The famous Shannon-Nyquist theorem has become a landmark in the development of digital signal processing. In modern applications, an increasingly number of functions is being pushed forward to sophisticated software algorithms, leaving only those delicate finely-tuned tasks for the circuit level. In this paper, we review sampling strategies which target reduction of the ADC rate below Nyquist. Our survey covers classic works from the early 50's of the previous century through recent publications from the past several years. The prime focus is bridging theory and practice, that is to pinpoint the potential of sub-Nyquist strategies to emerge from the math to the hardware. In that spirit, we integrate contemporary theoretical viewpoints, which study signal modeling in a union of subspaces, together with a taste of practical aspects, namely how the avant-garde modalities boil down to concrete signal processing systems. Our hope is that this presentation style will attract the interest of both researchers and engineers in the hope of promoting the sub-Nyquist premise into practical applications, and encouraging further research into this exciting new frontier.Comment: 48 pages, 18 figures, to appear in IEEE Signal Processing Magazin

Structured Compressed Sensing: From Theory to Applications

Compressed sensing (CS) is an emerging field that has attracted considerable research interest over the past few years. Previous review articles in CS limit their scope to standard discrete-to-discrete measurement architectures using matrices of randomized nature and signal models based on standard sparsity. In recent years, CS has worked its way into several new application areas. This, in turn, necessitates a fresh look on many of the basics of CS. The random matrix measurement operator must be replaced by more structured sensing architectures that correspond to the characteristics of feasible acquisition hardware. The standard sparsity prior has to be extended to include a much richer class of signals and to encode broader data models, including continuous-time signals. In our overview, the theme is exploiting signal and measurement structure in compressive sensing. The prime focus is bridging theory and practice; that is, to pinpoint the potential of structured CS strategies to emerge from the math to the hardware. Our summary highlights new directions as well as relations to more traditional CS, with the hope of serving both as a review to practitioners wanting to join this emerging field, and as a reference for researchers that attempts to put some of the existing ideas in perspective of practical applications.Comment: To appear as an overview paper in IEEE Transactions on Signal Processin

Verification of system properties of polynomial systems using discrete-time approximations and set-based analysis

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2015von Philipp Rumschinsk

Des structures verticales aux structures horizontales : Nouveaux défis d'optimisation sur les marchés de l'électricité

The electricity supply chain has seen a strong evolution of its environnement over the past years. Liberalization of electricity markets and new technologies are having a strong influence on how to organize electricity production and transmission. Previous computational methods used in electricity related problems need to be updated in order to follow the evolution of real life constraints. One classical problem for a generation company (GC) is the Unit Commitment problem (UC) which consists in establishing an electricity production plan over a given time horizon to sat isfy a demand in electricity. When first considered, the price of electricity and demands were relatively easy to estimate as national GCs had a monopoly over the market. This problem has been widely studied and solved using Mathematical Programming (MP) methods. Today, the price of electricity can be relatively volatile due to the introduction of deregulated electricity markets and the demand of the market is split among several independent GCs competing on several different markets. When estimating profit, a GC cannot therefore consider solving only a UC problem. There is a need to integrate the uncertainty on the price of electricity and the quantities to produce when a GC must take decisions in order to establish a production plan. Technology has also led to new conceptual organization in the electricity supply chain through Micro-Grids (MGs). A MG is composed of a group of power consumers which have their own power generation units and optimizes its internal electricity consumption. This concept is possible due to the increasing use of renewable energy sources and the increasing penetra tion of interconnected devices used in daily life. Still, because renewable energy sources are intermittent and storage devices are still not sufficiently efficient, MGs cannot consider being autonomous regarding electricity production. Therefore, MGs must have external power sup pliers to ensure sufficient electricity supply at all time. A GC trading electricity with a MG faces a lot of uncertainty regarding its demand because of the internal management of the MG. This situation asks again for new computational methods considering the interaction between different actors. We also face an increasing need of reliability in electricity transmission. Optimization prob xi lems related to transmission networks have also been studied for a long time as the UC. These optimization problems increasingly tend to consider robustness to deal with reliability issues. In this thesis, several optimization problems considering modern constraints related to the elec tricity supply chain are studied through MP. Several problems consider interactions between actors and are modelled through bi-level formulations. We illustrate how the difficulties in troduced by the evolving context can be used to derive properties of the models considered to reformulate them into mixed integer linear programs. Efficient heuristic methods are obtained inspired by the exact formulations proposed, some of which being applicable to more general problems. An extensive analysis of the performance of the solving methods as well as the influence of the parameters of the problems introduced by modern constraints are presented.La chaine d’approvisionnement énergétique a fortement évolué aux cours des 20 dernières années. La libéralisation des marchés de l’électricité et les nouvelles technologies ont fortement influencé la manière d’envisager la production et la transmission d’électricité. Les modèles mathématiques classiques utilisés dans les problèmes lié à l’énergie ont besoin d’être revus pour intégrer les contraintes pratiques modernes.Un problème classique pour un Compagnie Génératrice (CG) est le problème de Unit Commitment (UC) qui consiste à établir un plan de production pour une demande en électricité connue. Lorsque ce problème fut considéré, le prix de l’électricité et la demande étaient relativement simple à estimer comme une seule CG nationale avait le monopole du marché. Ce problème a été étudié de manière extensive en utilisant de la Programmation Mathématique (PM). Aujourd’hui, le prix de l’électricité est relativement volatile à cause de l’introduction de marchés dérégulés et la demande du marché est répartie entre plusieurs CGs en compétition sur divers marchés. Une CG ne peut se limiter à considérer un problème de UC seul pour envisager sa production. Il y a un besoin d’intégrer les incertitudes liées au marché de l’électricité et aux quantités à produire aux modèles utilisés pour qu’une CG puisse établir un plan de production rentable.La technologie a aussi permis d’envisager de nouveaux concept tel que les Micro-Grilles (MGs). Une MG est composée d’un ensemble de consommateurs reliés à travers un réseau de transmission, possédant des générateurs d’électricité et optimisant leur consommation interne. Ce concept est possible grâce à l’utilisation croissante d’énergies renouvelables locales ainsi que l’utilisant croissante d’appareils interconnectés. Cependant, étant donné que les énergies renouvelables ont un faible rendement, sont intermittentes et que les appareils de stockage d’énergie sont encore peu efficaces, les MGs ne peuvent pas envisager d’être pleinement autonome en électricité. Il y a donc une nécessité d’avoir un fournisseur d’électricité externe pour avoir suffisamment d’électricité disponible à tout moment. Une CG jouant le rôle de fournisseur auprès d’une MG fait face énormément d’incertitude concernant la demande à cause de la gestion interne de la MG sur laquelle elle n’a pas de contrôle.Dans cette thèse, des problèmes d’optimisation intégrant de nouvelles contraintes modernes liés à l’approvisionnement énergétique sont étudiés via la PM. Plusieurs problèmes considèrant des interactions entre plusieurs acteurs sont modélisés via des formulations bi-niveau. Nous illustrons comment les difficultés liées aux contraintes modernes peuvent être exploitées pour obtenir des propriétés permettant de reformuler les problèmes étudiés en formulation linéaire en nombre entiers. Des heuristiques performantes sont obtenus à partir des formulations exactes dont certaines sont applicables à des problèmes plus généraux. Une analyse extensive de la performance des méthodes de résolution ainsi que de l’influence des contraintes modernes sont présentées dans diverses expériences numériques

Regelungstheorie

The workshop “Regelungstheorie” (control theory) covered a broad variety of topics that were either concerned with fundamental mathematical aspects of control or with its strong impact in various fields of engineering

T-systems and Y-systems in integrable systems

The T and Y-systems are ubiquitous structures in classical and quantum integrable systems. They are difference equations having a variety of aspects related to commuting transfer matrices in solvable lattice models, q-characters of Kirillov-Reshetikhin modules of quantum affine algebras, cluster algebras with coefficients, periodicity conjectures of Zamolodchikov and others, dilogarithm identities in conformal field theory, difference analogue of L-operators in KP hierarchy, Stokes phenomena in 1d Schr\"odinger problem, AdS/CFT correspondence, Toda field equations on discrete space-time, Laplace sequence in discrete geometry, Fermionic character formulas and combinatorial completeness of Bethe ansatz, Q-system and ideal gas with exclusion statistics, analytic and thermodynamic Bethe ans\"atze, quantum transfer matrix method and so forth. This review article is a collection of short reviews on these topics which can be read more or less independently.Comment: 156 pages. Minor corrections including the last paragraph of sec.3.5, eqs.(4.1), (5.28), (9.37) and (13.54). The published version (JPA topical review) also needs these correction