TY - JOUR A1 - Acevedo, Walter A1 - Reich, Sebastian A1 - Cubasch, Ulrich T1 - Towards the assimilation of tree-ring-width records using ensemble Kalman filtering techniques JF - Climate dynamics : observational, theoretical and computational research on the climate system N2 - This paper investigates the applicability of the Vaganov–Shashkin–Lite (VSL) forward model for tree-ring-width chronologies as observation operator within a proxy data assimilation (DA) setting. Based on the principle of limiting factors, VSL combines temperature and moisture time series in a nonlinear fashion to obtain simulated TRW chronologies. When used as observation operator, this modelling approach implies three compounding, challenging features: (1) time averaging, (2) “switching recording” of 2 variables and (3) bounded response windows leading to “thresholded response”. We generate pseudo-TRW observations from a chaotic 2-scale dynamical system, used as a cartoon of the atmosphere-land system, and attempt to assimilate them via ensemble Kalman filtering techniques. Results within our simplified setting reveal that VSL’s nonlinearities may lead to considerable loss of assimilation skill, as compared to the utilization of a time-averaged (TA) linear observation operator. In order to understand this undesired effect, we embed VSL’s formulation into the framework of fuzzy logic (FL) theory, which thereby exposes multiple representations of the principle of limiting factors. DA experiments employing three alternative growth rate functions disclose a strong link between the lack of smoothness of the growth rate function and the loss of optimality in the estimate of the TA state. Accordingly, VSL’s performance as observation operator can be enhanced by resorting to smoother FL representations of the principle of limiting factors. This finding fosters new interpretations of tree-ring-growth limitation processes. KW - Proxy forward modeling KW - Data assimilation KW - Fuzzy logic KW - Ensemble Kalman filter KW - Paleoclimate reconstruction Y1 - 2016 U6 - https://doi.org/10.1007/s00382-015-2683-1 SN - 0930-7575 SN - 1432-0894 VL - 46 SP - 1909 EP - 1920 PB - Springer CY - New York ER - TY - INPR A1 - Alsaedy, Ammar T1 - Variational primitive of a differential form N2 - In this paper we specify the Dirichlet to Neumann operator related to the Cauchy problem for the gradient operator with data on a part of the boundary. To this end, we consider a nonlinear relaxation of this problem which is a mixed boundary problem of Zaremba type for the p-Laplace equation. T3 - Preprints des Instituts für Mathematik der Universität Potsdam - 5 (2016) 4 KW - Dirichlet-to-Neumann operator KW - Cauchy problem KW - p-Laplace operator KW - calculus of variations Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-89223 SN - 2193-6943 VL - 5 IS - 4 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - INPR A1 - Alsaedy, Ammar A1 - Tarkhanov, Nikolai Nikolaevich T1 - A Hilbert boundary value problem for generalised Cauchy-Riemann equations N2 - We elaborate a boundary Fourier method for studying an analogue of the Hilbert problem for analytic functions within the framework of generalised Cauchy-Riemann equations. The boundary value problem need not satisfy the Shapiro-Lopatinskij condition and so it fails to be Fredholm in Sobolev spaces. We show a solvability condition of the Hilbert problem, which looks like those for ill-posed problems, and construct an explicit formula for approximate solutions. T3 - Preprints des Instituts für Mathematik der Universität Potsdam - 5 (2016) 1 KW - Dirac operator KW - Clifford algebra KW - Riemann-Hilbert problem KW - Fredholm operator Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-86109 SN - 2193-6943 VL - 5 IS - 1 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Antonini, Paolo A1 - Azzali, Sara A1 - Skandalis, Georges T1 - Bivariant K-theory with R/Z-coefficients and rho classes of unitary representations JF - Journal of functional analysis N2 - We construct equivariant KK-theory with coefficients in and R/Z as suitable inductive limits over II1-factors. We show that the Kasparov product, together with its usual functorial properties, extends to KK-theory with real coefficients. Let Gamma be a group. We define a Gamma-algebra A to be K-theoretically free and proper (KFP) if the group trace tr of Gamma acts as the unit element in KKR Gamma (A, A). We show that free and proper Gamma-algebras (in the sense of Kasparov) have the (KFP) property. Moreover, if Gamma is torsion free and satisfies the KK Gamma-form of the Baum-Connes conjecture, then every Gamma-algebra satisfies (KFP). If alpha : Gamma -> U-n is a unitary representation and A satisfies property (KFP), we construct in a canonical way a rho class rho(A)(alpha) is an element of KKR/Z1,Gamma (A A) This construction generalizes the Atiyah-Patodi-Singer K-theory class with R/Z-coefficients associated to alpha. (C) 2015 Elsevier Inc. All rights reserved. KW - Operator algebras KW - Bivariant K-theory KW - Rho invariants Y1 - 2016 U6 - https://doi.org/10.1016/j.jfa.2015.06.017 SN - 0022-1236 SN - 1096-0783 VL - 270 SP - 447 EP - 481 PB - Elsevier CY - San Diego ER - TY - JOUR A1 - Becker, Christian T1 - Cheeger-Chern-Simons Theory and Differential String Classes JF - Annales de l'Institut Henri Poincaré N2 - We construct new concrete examples of relative differential characters, which we call Cheeger-Chern-Simons characters. They combine the well-known Cheeger-Simons characters with Chern-Simons forms. In the same way as Cheeger-Simons characters generalize Chern-Simons invariants of oriented closed manifolds, Cheeger-Chern-Simons characters generalize Chern-Simons invariants of oriented manifolds with boundary. We study the differential cohomology of compact Lie groups G and their classifying spaces BG. We show that the even degree differential cohomology of BG canonically splits into Cheeger-Simons characters and topologically trivial characters. We discuss the transgression in principal G-bundles and in the universal bundle. We introduce two methods to lift the universal transgression to a differential cohomology valued map. They generalize the Dijkgraaf-Witten correspondence between 3-dimensional Chern-Simons theories and Wess-Zumino-Witten terms to fully extended higher-order Chern-Simons theories. Using these lifts, we also prove two versions of a differential Hopf theorem. Using Cheeger-Chern-Simons characters and transgression, we introduce the notion of differential trivializations of universal characteristic classes. It generalizes well-established notions of differential String classes to arbitrary degree. Specializing to the class , we recover isomorphism classes of geometric string structures on Spin (n) -bundles with connection and the corresponding spin structures on the free loop space. The Cheeger-Chern-Simons character associated with the class together with its transgressions to loop space and higher mapping spaces defines a Chern-Simons theory, extended down to points. Differential String classes provide trivializations of this extended Chern-Simons theory. This setting immediately generalizes to arbitrary degree: for any universal characteristic class of principal G-bundles, we have an associated Cheeger-Chern-Simons character and extended Chern-Simons theory. Differential trivialization classes yield trivializations of this extended Chern-Simons theory. Y1 - 2016 U6 - https://doi.org/10.1007/s00023-016-0485-6 SN - 1424-0637 SN - 1424-0661 VL - 17 SP - 1529 EP - 1594 PB - Springer CY - Basel ER - TY - JOUR A1 - Beinrucker, Andre A1 - Dogan, Urun A1 - Blanchard, Gilles T1 - Extensions of stability selection using subsamples of observations and covariates JF - Statistics and Computing N2 - We introduce extensions of stability selection, a method to stabilise variable selection methods introduced by Meinshausen and Buhlmann (J R Stat Soc 72:417-473, 2010). We propose to apply a base selection method repeatedly to random subsamples of observations and subsets of covariates under scrutiny, and to select covariates based on their selection frequency. We analyse the effects and benefits of these extensions. Our analysis generalizes the theoretical results of Meinshausen and Buhlmann (J R Stat Soc 72:417-473, 2010) from the case of half-samples to subsamples of arbitrary size. We study, in a theoretical manner, the effect of taking random covariate subsets using a simplified score model. Finally we validate these extensions on numerical experiments on both synthetic and real datasets, and compare the obtained results in detail to the original stability selection method. KW - Variable selection KW - Stability selection KW - Subsampling Y1 - 2016 U6 - https://doi.org/10.1007/s11222-015-9589-y SN - 0960-3174 SN - 1573-1375 VL - 26 SP - 1059 EP - 1077 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Benini, Marco T1 - Optimal space of linear classical observables for Maxwell k-forms via spacelike and timelike compact de Rham cohomologies JF - Journal of mathematical physics N2 - Being motivated by open questions in gauge field theories, we consider non-standard de Rham cohomology groups for timelike compact and spacelike compact support systems. These cohomology groups are shown to be isomorphic respectively to the usual de Rham cohomology of a spacelike Cauchy surface and its counterpart with compact support. Furthermore, an analog of the usual Poincare duality for de Rham cohomology is shown to hold for the case with non-standard supports as well. We apply these results to find optimal spaces of linear observables for analogs of arbitrary degree k of both the vector potential and the Faraday tensor. The term optimal has to be intended in the following sense: The spaces of linear observables we consider distinguish between different configurations; in addition to that, there are no redundant observables. This last point in particular heavily relies on the analog of Poincare duality for the new cohomology groups. Published by AIP Publishing. Y1 - 2016 U6 - https://doi.org/10.1063/1.4947563 SN - 0022-2488 SN - 1089-7658 VL - 57 SP - 1249 EP - 1279 PB - American Institute of Physics CY - Melville ER - TY - THES A1 - Berner, Nadine T1 - Deciphering multiple changes in complex climate time series using Bayesian inference T1 - Bayes'sche Inferenz als diagnostischer Ansatz zur Untersuchung multipler Übergänge in komplexen Klimazeitreihen N2 - Change points in time series are perceived as heterogeneities in the statistical or dynamical characteristics of the observations. Unraveling such transitions yields essential information for the understanding of the observed system’s intrinsic evolution and potential external influences. A precise detection of multiple changes is therefore of great importance for various research disciplines, such as environmental sciences, bioinformatics and economics. The primary purpose of the detection approach introduced in this thesis is the investigation of transitions underlying direct or indirect climate observations. In order to develop a diagnostic approach capable to capture such a variety of natural processes, the generic statistical features in terms of central tendency and dispersion are employed in the light of Bayesian inversion. In contrast to established Bayesian approaches to multiple changes, the generic approach proposed in this thesis is not formulated in the framework of specialized partition models of high dimensionality requiring prior specification, but as a robust kernel-based approach of low dimensionality employing least informative prior distributions. First of all, a local Bayesian inversion approach is developed to robustly infer on the location and the generic patterns of a single transition. The analysis of synthetic time series comprising changes of different observational evidence, data loss and outliers validates the performance, consistency and sensitivity of the inference algorithm. To systematically investigate time series for multiple changes, the Bayesian inversion is extended to a kernel-based inference approach. By introducing basic kernel measures, the weighted kernel inference results are composed into a proxy probability to a posterior distribution of multiple transitions. The detection approach is applied to environmental time series from the Nile river in Aswan and the weather station Tuscaloosa, Alabama comprising documented changes. The method’s performance confirms the approach as a powerful diagnostic tool to decipher multiple changes underlying direct climate observations. Finally, the kernel-based Bayesian inference approach is used to investigate a set of complex terrigenous dust records interpreted as climate indicators of the African region of the Plio-Pleistocene period. A detailed inference unravels multiple transitions underlying the indirect climate observations, that are interpreted as conjoint changes. The identified conjoint changes coincide with established global climate events. In particular, the two-step transition associated to the establishment of the modern Walker-Circulation contributes to the current discussion about the influence of paleoclimate changes on the environmental conditions in tropical and subtropical Africa at around two million years ago. N2 - Im Allgemeinen stellen punktuelle Veränderungen in Zeitreihen (change points) eine Heterogenität in den statistischen oder dynamischen Charakteristika der Observablen dar. Das Auffinden und die Beschreibung solcher Übergänge bietet grundlegende Informationen über das beobachtete System hinsichtlich seiner intrinsischen Entwicklung sowie potentieller externer Einflüsse. Eine präzise Detektion von Veränderungen ist daher für die verschiedensten Forschungsgebiete, wie den Umweltwissenschaften, der Bioinformatik und den Wirtschaftswissenschaften von großem Interesse. Die primäre Zielsetzung der in der vorliegenden Doktorarbeit vorgestellten Detektionsmethode ist die Untersuchung von direkten als auch indirekten Klimaobservablen auf Veränderungen. Um die damit verbundene Vielzahl an möglichen natürlichen Prozessen zu beschreiben, werden im Rahmen einer Bayes’schen Inversion die generischen statistischen Merkmale Zentraltendenz und Dispersion verwendet. Im Gegensatz zu etablierten Bayes’schen Methoden zur Analyse von multiplen Übergängen, die im Rahmen von Partitionsmodellen hoher Dimensionalität formuliert sind und die Spezifikation von Priorverteilungen erfordern, wird in dieser Doktorarbeit ein generischer, Kernel-basierter Ansatz niedriger Dimensionalität mit minimal informativen Priorverteilungen vorgestellt. Zunächst wird ein lokaler Bayes’scher Inversionsansatz entwickelt, der robuste Rückschlüsse auf die Position und die generischen Charakteristika einer einzelnen Veränderung erlaubt. Durch die Analyse von synthetischen Zeitreihen die dem Einfluss von Veränderungen unterschiedlicher Signifikanz, Datenverlust und Ausreißern unterliegen wird die Leistungsfähigkeit, Konsistenz und Sensitivität der Inversionmethode begründet. Um Zeitreihen auch auf multiple Veränderungen systematisch untersuchen zu können, wird die Methode der Bayes’schen Inversion zu einem Kernel-basierten Ansatz erweitert. Durch die Einführung grundlegender Kernel-Maße können die Kernel-Resultate zu einer gewichteten Wahrscheinlichkeit kombiniert werden die als Proxy einer Posterior-Verteilung multipler Veränderungen dient. Der Detektionsalgorithmus wird auf reale Umweltmessreihen vom Nil-Fluss in Aswan und von der Wetterstation Tuscaloosa, Alabama, angewendet, die jeweils dokumentierte Veränderungen enthalten. Das Ergebnis dieser Analyse bestätigt den entwickelten Ansatz als eine leistungsstarke diagnostische Methode zur Detektion multipler Übergänge in Zeitreihen. Abschließend wird der generische Kernel-basierte Bayes’sche Ansatz verwendet, um eine Reihe von komplexen terrigenen Staubdaten zu untersuchen, die als Klimaindikatoren der afrikanischen Region des Plio-Pleistozän interpretiert werden. Eine detaillierte Untersuchung deutet auf multiple Veränderungen in den indirekten Klimaobservablen hin, von denen einige als gemeinsame Übergänge interpretiert werden. Diese gemeinsam auftretenden Ereignisse stimmen mit etablierten globalen Klimaereignissen überein. Insbesondere der gefundene Zwei-Stufen-Übergang, der mit der Ausbildung der modernen Walker-Zirkulation assoziiert wird, liefert einen wichtigen Beitrag zur aktuellen Diskussion über den Einfluss von paläoklimatischen Veränderungen auf die Umweltbedingungen im tropischen und subtropischen Afrika vor circa zwei Millionen Jahren. KW - kernel-based Bayesian inference KW - multi-change point detection KW - direct and indirect climate observations KW - Plio-Pleistocene KW - (sub-) tropical Africa KW - terrigenous dust KW - kernel-basierte Bayes'sche Inferenz KW - Detektion multipler Übergänge KW - direkte und indirekte Klimaobservablen KW - Plio-Pleistozän KW - (sub-) tropisches Afrika KW - terrigener Staub Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-100065 ER - TY - JOUR A1 - Blanchard, Gilles A1 - Flaska, Marek A1 - Handy, Gregory A1 - Pozzi, Sara A1 - Scott, Clayton T1 - Classification with asymmetric label noise: Consistency and maximal denoising JF - Electronic journal of statistics N2 - In many real-world classification problems, the labels of training examples are randomly corrupted. Most previous theoretical work on classification with label noise assumes that the two classes are separable, that the label noise is independent of the true class label, or that the noise proportions for each class are known. In this work, we give conditions that are necessary and sufficient for the true class-conditional distributions to be identifiable. These conditions are weaker than those analyzed previously, and allow for the classes to be nonseparable and the noise levels to be asymmetric and unknown. The conditions essentially state that a majority of the observed labels are correct and that the true class-conditional distributions are "mutually irreducible," a concept we introduce that limits the similarity of the two distributions. For any label noise problem, there is a unique pair of true class-conditional distributions satisfying the proposed conditions, and we argue that this pair corresponds in a certain sense to maximal denoising of the observed distributions. Our results are facilitated by a connection to "mixture proportion estimation," which is the problem of estimating the maximal proportion of one distribution that is present in another. We establish a novel rate of convergence result for mixture proportion estimation, and apply this to obtain consistency of a discrimination rule based on surrogate loss minimization. Experimental results on benchmark data and a nuclear particle classification problem demonstrate the efficacy of our approach. KW - Classification KW - label noise KW - mixture proportion estimation KW - surrogate loss KW - consistency Y1 - 2016 U6 - https://doi.org/10.1214/16-EJS1193 SN - 1935-7524 VL - 10 SP - 2780 EP - 2824 PB - Institute of Mathematical Statistics CY - Cleveland ER - TY - JOUR A1 - Blanchard, Gilles A1 - Kraemer, Nicole T1 - Convergence rates of Kernel Conjugate Gradient for random design regression JF - Analysis and applications N2 - We prove statistical rates of convergence for kernel-based least squares regression from i.i.d. data using a conjugate gradient (CG) algorithm, where regularization against over-fitting is obtained by early stopping. This method is related to Kernel Partial Least Squares, a regression method that combines supervised dimensionality reduction with least squares projection. Following the setting introduced in earlier related literature, we study so-called "fast convergence rates" depending on the regularity of the target regression function (measured by a source condition in terms of the kernel integral operator) and on the effective dimensionality of the data mapped into the kernel space. We obtain upper bounds, essentially matching known minimax lower bounds, for the L-2 (prediction) norm as well as for the stronger Hilbert norm, if the true regression function belongs to the reproducing kernel Hilbert space. If the latter assumption is not fulfilled, we obtain similar convergence rates for appropriate norms, provided additional unlabeled data are available. KW - Nonparametric regression KW - reproducing kernel Hilbert space KW - conjugate gradient KW - partial least squares KW - minimax convergence rates Y1 - 2016 U6 - https://doi.org/10.1142/S0219530516400017 SN - 0219-5305 SN - 1793-6861 VL - 14 SP - 763 EP - 794 PB - World Scientific CY - Singapore ER - TY - INPR A1 - Blanchard, Gilles A1 - Krämer, Nicole T1 - Convergence rates of kernel conjugate gradient for random design regression N2 - We prove statistical rates of convergence for kernel-based least squares regression from i.i.d. data using a conjugate gradient algorithm, where regularization against overfitting is obtained by early stopping. This method is related to Kernel Partial Least Squares, a regression method that combines supervised dimensionality reduction with least squares projection. Following the setting introduced in earlier related literature, we study so-called "fast convergence rates" depending on the regularity of the target regression function (measured by a source condition in terms of the kernel integral operator) and on the effective dimensionality of the data mapped into the kernel space. We obtain upper bounds, essentially matching known minimax lower bounds, for the L^2 (prediction) norm as well as for the stronger Hilbert norm, if the true regression function belongs to the reproducing kernel Hilbert space. If the latter assumption is not fulfilled, we obtain similar convergence rates for appropriate norms, provided additional unlabeled data are available. T3 - Preprints des Instituts für Mathematik der Universität Potsdam - 5 (2016) 8 KW - nonparametric regression KW - reproducing kernel Hilbert space KW - conjugate gradient KW - partial least squares KW - minimax convergence rates Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-94195 SN - 2193-6943 VL - 5 IS - 8 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - INPR A1 - Blanchard, Gilles A1 - Mücke, Nicole T1 - Optimal rates for regularization of statistical inverse learning problems N2 - We consider a statistical inverse learning problem, where we observe the image of a function f through a linear operator A at i.i.d. random design points X_i, superposed with an additional noise. The distribution of the design points is unknown and can be very general. We analyze simultaneously the direct (estimation of Af) and the inverse (estimation of f) learning problems. In this general framework, we obtain strong and weak minimax optimal rates of convergence (as the number of observations n grows large) for a large class of spectral regularization methods over regularity classes defined through appropriate source conditions. This improves on or completes previous results obtained in related settings. The optimality of the obtained rates is shown not only in the exponent in n but also in the explicit dependence of the constant factor in the variance of the noise and the radius of the source condition set. T3 - Preprints des Instituts für Mathematik der Universität Potsdam - 5 (2016) 5 KW - statistical inverse problem KW - minimax rate KW - kernel method Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-89782 SN - 2193-6943 VL - 5 IS - 5 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Bomanson, Jori A1 - Janhunen, Tomi A1 - Schaub, Torsten H. A1 - Gebser, Martin A1 - Kaufmann, Benjamin T1 - Answer Set Programming Modulo Acyclicity JF - Fundamenta informaticae N2 - Acyclicity constraints are prevalent in knowledge representation and applications where acyclic data structures such as DAGs and trees play a role. Recently, such constraints have been considered in the satisfiability modulo theories (SMT) framework, and in this paper we carry out an analogous extension to the answer set programming (ASP) paradigm. The resulting formalism, ASP modulo acyclicity, offers a rich set of primitives to express constraints related to recursive structures. In the technical results of the paper, we relate the new generalization with standard ASP by showing (i) how acyclicity extensions translate into normal rules, (ii) how weight constraint programs can be instrumented by acyclicity extensions to capture stability in analogy to unfounded set checking, and (iii) how the gap between supported and stable models is effectively closed in the presence of such an extension. Moreover, we present an efficient implementation of acyclicity constraints by incorporating a respective propagator into the state-of-the-art ASP solver CLASP. The implementation provides a unique combination of traditional unfounded set checking with acyclicity propagation. In the experimental part, we evaluate the interplay of these orthogonal checks by equipping logic programs with supplementary acyclicity constraints. The performance results show that native support for acyclicity constraints is a worthwhile addition, furnishing a complementary modeling construct in ASP itself as well as effective means for translation-based ASP solving. Y1 - 2016 U6 - https://doi.org/10.3233/FI-2016-1398 SN - 0169-2968 SN - 1875-8681 VL - 147 SP - 63 EP - 91 PB - IOS Press CY - Amsterdam ER - TY - JOUR A1 - Bär, Christian A1 - Strohmaier, Alexander T1 - A Rigorous Geometric Derivation of the Chiral Anomaly in Curved Backgrounds JF - Communications in mathematical physics N2 - We discuss the chiral anomaly for a Weyl field in a curved background and show that a novel index theorem for the Lorentzian Dirac operator can be applied to describe the gravitational chiral anomaly. A formula for the total charge generated by the gravitational and gauge field background is derived directly in Lorentzian signature and in a mathematically rigorous manner. It contains a term identical to the integrand in the Atiyah-Singer index theorem and another term involving the.-invariant of the Cauchy hypersurfaces. Y1 - 2016 U6 - https://doi.org/10.1007/s00220-016-2664-1 SN - 0010-3616 SN - 1432-0916 VL - 347 SP - 703 EP - 721 PB - Springer CY - New York ER - TY - JOUR A1 - Bärenzung, Julien A1 - Holschneider, Matthias A1 - Lesur, Vincent T1 - constraints JF - Journal of geophysical research : Solid earth N2 - Prior information in ill-posed inverse problem is of critical importance because it is conditioning the posterior solution and its associated variability. The problem of determining the flow evolving at the Earth's core-mantle boundary through magnetic field models derived from satellite or observatory data is no exception to the rule. This study aims to estimate what information can be extracted on the velocity field at the core-mantle boundary, when the frozen flux equation is inverted under very weakly informative, but realistic, prior constraints. Instead of imposing a converging spectrum to the flow, we simply assume that its poloidal and toroidal energy spectra are characterized by power laws. The parameters of the spectra, namely, their magnitudes, and slopes are unknown. The connection between the velocity field, its spectra parameters, and the magnetic field model is established through the Bayesian formulation of the problem. Working in two steps, we determined the time-averaged spectra of the flow within the 2001–2009.5 period, as well as the flow itself and its associated uncertainties in 2005.0. According to the spectra we obtained, we can conclude that the large-scale approximation of the velocity field is not an appropriate assumption within the time window we considered. For the flow itself, we show that although it is dominated by its equatorial symmetric component, it is very unlikely to be perfectly symmetric. We also demonstrate that its geostrophic state is questioned in different locations of the outer core. Y1 - 2016 U6 - https://doi.org/10.1002/2015JB012464 SN - 2169-9313 SN - 2169-9356 VL - 121 SP - 1343 EP - 1364 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Cattiaux, Patrick A1 - Fradon, Myriam A1 - Kulik, Alexei M. A1 - Roelly, Sylvie T1 - Long time behavior of stochastic hard ball systems JF - Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability N2 - We study the long time behavior of a system of n = 2, 3 Brownian hard balls, living in R-d for d >= 2, submitted to a mutual attraction and to elastic collisions. KW - hard core interaction KW - local time KW - Lyapunov function KW - normal reflection KW - Poincare inequality KW - reversible measure KW - stochastic differential equations Y1 - 2016 U6 - https://doi.org/10.3150/14-BEJ672 SN - 1350-7265 SN - 1573-9759 VL - 22 SP - 681 EP - 710 PB - International Statistical Institute CY - Voorburg ER - TY - JOUR A1 - Chang, D. -C. A1 - Viahmoudi, M. Hedayat A1 - Schulze, Bert-Wolfgang T1 - PSEUDO-DIFFERENTIAL ANALYSIS WITH TWISTED SYMBOLIC STRUCTURE JF - Journal of nonlinear and convex analysis : an international journal N2 - This paper is devoted to pseudo-differential operators and new applications. We establish necessary extensions of the standard calculus to specific classes of operator-valued symbols occurring in principal symbolic hierarchies of operators on manifolds with singularities or stratified spaces. KW - Pseudo-differential operators KW - boundary value problems KW - operator valued symbols KW - Fourier transform Y1 - 2016 SN - 1345-4773 SN - 1880-5221 VL - 17 SP - 1889 EP - 1937 PB - Yokohama Publishers CY - Yokohama ER - TY - THES A1 - Cheng, Yuan T1 - Recursive state estimation in dynamical systems Y1 - 2016 ER - TY - THES A1 - Chutsagulprom, Nawinda T1 - Ensemble-based filters dealing with non-Gaussianity and nonlinearity Y1 - 2016 ER - TY - JOUR A1 - Denecke, Klaus-Dieter T1 - The partial clone of linear terms JF - Siberian Mathematical Journal N2 - Generalizing a linear expression over a vector space, we call a term of an arbitrary type tau linear if its every variable occurs only once. Instead of the usual superposition of terms and of the total many-sorted clone of all terms in the case of linear terms, we define the partial many-sorted superposition operation and the partial many-sorted clone that satisfies the superassociative law as weak identity. The extensions of linear hypersubstitutions are weak endomorphisms of this partial clone. For a variety V of one-sorted total algebras of type tau, we define the partial many-sorted linear clone of V as the partial quotient algebra of the partial many-sorted clone of all linear terms by the set of all linear identities of V. We prove then that weak identities of this clone correspond to linear hyperidentities of V. KW - linear term KW - clone KW - partial clone KW - linear hypersubstitution KW - linear identity KW - linear hyperidentity Y1 - 2016 U6 - https://doi.org/10.1134/S0037446616040030 SN - 0037-4466 SN - 1573-9260 VL - 57 SP - 589 EP - 598 PB - Pleiades Publ. CY - New York ER -