785 research outputs found
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Analytical validation of innovative magneto-inertial outcomes: a controlled environment study.
peer reviewe
Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5
This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered.
First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes.
Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification.
Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well
Circulation Statistics in Homogeneous and Isotropic Turbulence
This is the committee version of a Thesis presented to the PostGrad Program
in Physics of the Physics Institute of the Federal University of Rio de Janeiro
(UFRJ), as a necessary requirement for the title of Ph.D. in Science (Physics).
The development of the Vortex Gas Model (VGM) introduces a novel statistical
framework for describing the characteristics of velocity circulation. In this
model, the underlying foundations rely on the statistical attributes of two
fundamental constituents. The first is a GMC field that governs intermittent
behavior and the second constituent is a Gaussian Free field responsible for
the partial polarization of the vortices in the gas. The model is revisited in
a more sophisticated language, where volume exclusion among vortices is
addressed. These additions were subsequently validated through numerical
simulations of turbulent Navier-Stokes equations. This revised approach
harmonizes with the multifractal characteristics exhibited by circulation
statistics, offering a compelling elucidation for the phenomenon of
linearization of the statistical circulation moments, observed in recent
numerical simulation.
In the end, a field theoretical approach, known as
Martin-Siggia-Rose-Janssen-de Dominicis (MSRJD) functional method is carried
out in the context of circulation probability density function. This approach
delves into the realm of extreme circulation events, often referred to as
Instantons, through two distinct methodologies: The First investigates the
linear solutions and, by a renormalization group argument a time-rescaling
symmetry is discussed. Secondly, a numerical strategy is implemented to tackle
the nonlinear instanton equations in the axisymmetric approximation. This
approach addresses the typical topology exhibited by the velocity field
associated with extreme circulation events.Comment: Ph.D. Thesis - preliminary versio
Time-delay interferometric ranging for LISA: Statistical analysis of bias-free ranging using laser noise minimization
Die Laser Interferometer Space Antenna (LISA) ist eine Mission der europäischen Weltraumagentur (ESA) zur Detektion von Gravitationswellen im Frequenzbereich zwischen 10^-4 Hz und 1 Hz. Gravitationswellen induzieren relative Abstandsänderungen, die LISA mithilfe von Laserinterferometrie mit Picometerpräzision misst. Ein großes Problem hierbei ist das Frequenzrauschen der Laser. Um dieses zu unterdrücken, ist es notwendig, mithilfe eines Algorithmus namens TDI (engl. time-delay interferometry), virtuelle Interferometer mit gleichlangen Armen zu konstruieren, wie z.B. das klassische Michelson-Interferometer.
In dieser Arbeit untersuchen wir die Performanz von TDI unter realistischen Bedingungen und identifizieren verschiedene Kopplungsmechanismen des Laserfrequenzrauschens. Als erstes betrachten wir die Datenverarbeitung an Bord der Satelliten, die benötigt wird, um die Abtastrate der interferometrischen Messungen zu reduzieren. Hierfür sind Anti-Alias-Filter vorgesehen, die der Faltung von Laserrauschleistung in das Beobachtungsband vorbeugen. Außerdem wirkt sich die Ebenheit der Filter auf die Effektivität von TDI aus (engl. flexing-filtering-effect). Dieser Effekt ist bereits in der Literatur beschrieben und wir demonstrieren in dieser Arbeit die Möglichkeit, ihn mithilfe von Kompensationsfiltern effektiv zu reduzieren. Als zweites betrachten wir Kopplungsmechanismen von Laserfrequenzrauschen im TDI-Algorithmus selbst. Fehler in der Interpolation der interferometrischen Messungen und Ungenauigkeiten in den absoluten Abstandsmessungen zwischen den Satelliten führen ebenfalls zu einer unzureichenden Reduzierung des Laserfrequenzrauschens. Wir beschreiben die oben genannten Kopplungsmechanismen analytisch und validieren die zugrundeliegenden Modelle mithilfe von numerischen Simulationen. Das tiefere Verständnis dieser Residuen ermöglicht es uns, geeignete instrumentelle Parameter zu wählen, die von hoher Relevanz für das Missionsdesign von LISA sind.
Des Weiteren beschäftigen wir uns in dieser Arbeit mit der möglichst genauen Bestimmung der absoluten Abständen zwischen den Satelliten, die für den TDI Algorithmus erforderlich sind. Hierfür werden die Abstandsinformationen aus den Seitenbändern und der PRN-Modulation (engl. pseudo-random noise) kombiniert. Wir zeigen, dass die PRN-Messung von systematischen Verzerrungen betroffen ist, die zu Laserrauschresiduen in den TDI-Variablen führen. Um diesen Fehler zu korrigieren, schlagen wir als zusätzliche Abstandsmessung TDI-Ranging (TDI-R) vor. TDI-R ist zwar ungenauer, aber frei von systematischen Verzerrungen und kann daher zur Kalibrierung der PRN-Messungen herangezogen werden. Wir präsentieren in dieser Arbeit eine ausführliche statistische Studie, um die Performanz von TDI-R zu charakterisieren. Dafür formulieren wir die Likelihood-Funktion der interferometrischen Messungen und berechnen die Fisher-Informationsmatrix, um die theoretisch mögliche untere Grenze der Schätzvarianz zu finden. Diese verhält sich invers proportional zur Integrationszeit und dem Verhältnis von Sekundärrauschleistung, die die interferometrische Messung fundamental limitiert, und Laserrauschleistung. Zusätzlich validieren wir die analytische untere Grenze der Schätzvarianz mithilfe von numerischen Simulationen und zeigen damit, dass unsere Implementierung von TDI-R optimal ist. Der entwickelte TDI-R-Algorithmus wird Teil der Datenverarbeitungspipeline sein und Konsistenzprüfungen und Kalibrierung der primären Abstandsmessmethoden ermöglichen.The Laser Interferometer Space Antenna (LISA) is a future ESA-led space-based observatory to explore the gravitational universe in the frequency band between 10^-4 Hz and 1 Hz. LISA implements picometer-precise inter-satellite ranging to measure tiny ripples in spacetime induced by gravitational waves (GWs). However, the single-link measurements are dominated by laser frequency noise, which is about nine orders of magnitude larger than the GW signals. Therefore, in post-processing, the time-delay interferometry (TDI) algorithm is used to synthesize virtual equal-arm interferometers to suppress laser frequency noise.
In this work we identify several laser frequency noise coupling channels that limit the performance of TDI. First, the on-board processing, which is used to decimate the sampling rate from tens of megahertz down to the telemetry rate of a few hertz, requires careful design. Appropriate anti-aliasing filters must be implemented to mitigate folding of laser noise power into the observation band. Furthermore, the flatness of these filters is important to limit the impact of the flexing-filtering effect. We demonstrate that this effect can be effectively reduced by using compensation filters on ground. Second, the post-processing delays applied in TDI are subject to interpolation and ranging errors. We study these laser and timing noise residuals analytically and perform simulations to validate the models numerically. Our findings have direct implications for the design of the LISA instrument as we identify the instrumental parameters that are essential for successful laser noise suppression and provide methods for designing appropriate filters for the on-board processing.
In addition, we discuss a dedicated ranging processing pipeline that produces high-precision range estimates that are the input for TDI by combining the sideband and pseudo-random noise (PRN) ranges. We show in this thesis that biases in the PRN measurements limit the laser noise suppression performance. Therefore, we propose time-delay interferometric ranging (TDI-R) as a third ranging sensor to estimate bias-free ranges that can be used to calibrate the biases in the PRN measurements.
We present a thorough statistical study of TDI-R to evaluate its performance. Therefore, we formulate the likelihood function of the interferometric data and use the Fisher information formalism to find a lower bound on the estimation variance of the inter-satellite ranges. We find that the ranging uncertainty is proportional to the inverse of the integration time and the ratio of secondary noise power, that limits the interferometric readout, to the laser noise power. To validate our findings we implement prototype TDI-R pipelines and perform numerical simulations. We show that we are able to formulate optimal estimators of the unbiased range that reach the Cramér-Rao lower bound previously expressed analytically. The developed TDI-R pipeline will be integrated into the ranging processing pipeline to perform consistency checks and ensure well-calibrated inter-satellite ranges
Proceedings of the 8th Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE 2023)
This volume gathers the papers presented at the Detection and Classification of Acoustic Scenes and Events 2023 Workshop (DCASE2023), Tampere, Finland, during 21–22 September 2023
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
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