The diploma work deals with techniques of optical contactless distance and velocity measurement. A basic summary of the methods are involved. The problematic of interferometric methods for vibration measurements is analysed in detail. It contains division of interferometers, description of their function principles and also chapters dealing with elements used in interferometers such as lasers, photodetectors and elements in the ray optical way - polarizers, retarders, optical isolators. The vibration and length measurement methods are described, as well as the conception of homodyne and heterodyne detection. Part of this work focuses on the quadrature signal processing and on the proposal of algorithm for demodulation of velocity/displacement and undergoing simple motioning object deviation. This algorithm is implemented in Labview and the whole software instrument served also for visualisation of measured data of the interferometer model constructed in the laboratory. The way how to build up a model, its setting and two possible configurations suitable for homodyne detection are described. Model of interferometer is built-up on the optical breadboard. Particular components are fixed by the help of mounts. The model and software enable to measure the velocity and the vibration deviation with the light wavelength exactness. Functionality and the exactness of the laboratory model are verified by vibrometer. Effects on the measurement uncertainty are discussed here and ways how to restrain them are proposed.

The master’s thesis describes known methods of signal measurement using principle of synchronous detection. Various methods are presented, their principles are examined and the problems when using them are analyzed. Further, procedures for reduction of adverse effects are described also. Second part of this thesis is focused on the instrument design. The instrument is intended for detection and processing of the output signals in a given optometric system. The proposed device is designed to operate on the principle of synchronous detection method using a vector signal evaluation. Advantages and disadvantages are discussed below.

The paper is devoted to the foundation of approximation methods for integral equations of the form (aI+SbI+K)f=g, where S is the Cauchy singular integral operator on (-1,1) and K is a weakly singular integral operator. Here a,b,g are given functions on (-1,1) and the unknown function f on (-1,1) is looked for. It is assumed that a and b are real-valued and Hölder continuous functions on [-1,1] without common zeros and that g belongs to some weighted space of Hölder continuous functions. In particular, g may have a finite number of singularities. Based on known spectral properties of Cauchy singular integral operators approximation methods for the numerical solution of the above equation are constructed, where both aspects the theoretical convergence and the numerical practicability are taken into account. The weighted uniform convergence of these methods is studied using a general approach based on the theory of approximation spaces. With the help of this approach it is possible to prove simultaneously the stability, the convergence and results on the order of convergence of the approximation methods under consideration.

The K-distribution method is a fast approximative method used for calculating thermal infrared radiative transfer in the atmosphere, as opposed to the traditional Line-by-line method, which is precise, but very time-costly. Here we consider the atmosphere to consist of homogeneous and plane-parallel layers in local thermal equilibrium. This lets us use efficient upwards recursion for calculating the thermal infrared radiative transfer and ultimately the outgoing irradiance at the top of the atmosphere. Our specific implementation of the K-distribution method revolves around changing the integration space from the wavenumber domain to the g domain by employing Gauss-Legendre quadrature in two steps. The method is implemented in MATLAB and is shown to be several thousand times faster than the traditional Line-by-line method, with the relative error being only 3 % for the outgoing irradiance at the top of the atmosphere.

Lineare hyperbolische partielle Differentialgleichungen in homogenen Medien, beispielsweise die Wellengleichung, die die Ausbreitung und die Streuung akustischer Wellen beschreibt, können im Zeitbereich mit Hilfe von Randintegralgleichungen formuliert werden. Im ersten Hauptteil dieser Arbeit stellen wir eine effiziente Möglichkeit vor, numerische Approximationen solcher Gleichungen zu implementieren, wenn das Huygens-Prinzip nicht gilt. Wir nutzen die Faltungsquadraturmethode für die Zeitdiskretisierung und eine Galerkin-Randelement-Methode für die Raumdiskretisierung. Mit der Faltungsquadraturmethode geht eine diskrete Faltung der Faltungsgewichte mit der Randdichte einher. Bei Gültigkeit des Huygens-Prinzips konvergieren die Gewichte exponentiell gegen null, sofern der Index hinreichend groß ist. Im gegenteiligen Fall, das heißt bei geraden Raumdimensionen oder wenn Dämpfungseffekte auftreten, kann kein Verschwinden der Gewichte beobachtet werden. Das führt zu Schwierigkeiten bei der effizienten numerischen Behandlung. Im ersten Hauptteil dieser Arbeit zeigen wir, dass die Kerne der Faltungsgewichte in gewisser Weise die Fundamentallösung im Zeitbereich approximieren und dass dies auch zutrifft, wenn beide bezüglich der räumlichen Variablen abgeleitet werden. Da die Fundamentallösung zudem für genügend große Zeiten, etwa nachdem die Wellenfront vorbeigezogen ist, glatt ist, schließen wir Gleiches auch in Bezug auf die Faltungsgewichte, die wir folglich mit hoher Genauigkeit und wenigen Interpolationspunkten interpolieren können. Darüber hinaus weisen wir darauf hin, dass zur weiteren Einsparung von Speicherkapazitäten, insbesondere bei Langzeitexperimenten, der von Schädle et al. entwickelte schnelle Faltungsalgorithmus eingesetzt werden kann. Wir diskutieren eine effiziente Implementierung des Problems und zeigen Ergebnisse eines numerischen Langzeitexperimentes. Im zweiten Hauptteil dieser Arbeit beschäftigen wir uns mit Transmissionsproblemen der Wellengleichung im Freiraum. Solche Probleme werden gewöhnlich derart behandelt, dass der Freiraum, wenn nötig durch Einführen eines künstlichen Randes, in ein unbeschränktes Außengebiet und ein beschränktes Innengebiet geteilt wird mit dem Ziel, eventuelle Inhomogenitäten oder Nichtlinearitäten des Materials vollständig im Innengebiet zu konzentrieren. Wir werden eine Lösungsstrategie vorstellen, die es erlaubt, die aus der Teilung resultierenden Teilprobleme so weit wie möglich unabhängig voneinander zu behandeln. Die Kopplung der Teilprobleme erfolgt über Transmissionsbedingungen, die auf dem ihnen gemeinsamen Rand vorgegeben sind. Wir diskutieren ein Kopplungsverfahren, das auf verschiedene Diskretisierungsschemata für das Innen- und das Außengebiet zurückgreift. Wir werden insbesondere ein explizites Verfahren im Innengebiet einsetzen, im Gegensatz zum Außengebiet, bei dem wir ein auf ein Mehrschrittverfahren beruhendes Faltungsquadraturverfahren nutzen. Die Kopplung erfolgt nach der Strategie von Johnson und Nédélec, bei der die direkte Randintegralmethode zum Einsatz kommt. Diese Strategie führt auf ein unsymmetrische System. Wir analysieren das diskrete Problem hinsichtlich Stabilität und Konvergenz und unterstreichen die Einsatzfähigkeit des Kopplungsalgorithmus mit der Durchführung numerischer Experimente.

No description available.

This thesis presents the design, layout, and measurements of a bi-directional amplifier with variable vector (in-phase / quadrature) gain control that will be part of an electronically steered phased array system. The electronically steered phased array has many advantages over the conventional mechanically steered antennas including rapid scanning of the beam and adaptively creating nulls in desired locations. The 10-bit bi-directional Vector Variable Gain Amplifier (VVGA) is part of the transmit and receive module of each antenna element where transmit and receive functionality is determined through a simple switch. The VVGA performs amplification of the IF IQ pair by an adjustable complex coefficient. At receive, the VVGA functions as a Vector Variable Gain Current Amplifier (VVGCA) and at transmit, the VVGA functions as a Vector Variable Gain Transadmittance Amplifier (VVGTA). Design procedure, layout entry, schematic and parasitic extracted simulation results, and measurements are presented in this thesis.

Efficiently pricing multi-asset options is a challenging problem in computational finance. Although classical Fourier methods are extremely fast in pricing single asset options, maintaining the tractability of Fourier techniques for multi-asset option pricing is still an area of active research. Fourier methods rely on explicit knowledge of the characteristic function of the suitably stochastic price process, allowing for calculation of the option price by evaluation of multidimensional integral in the Fourier domain. The high smoothness of the integrand in the Fourier space motivates the exploration of deterministic quadrature methods that are highly efficient under certain regularity assumptions, such as, adaptive sparse grids quadrature (ASGQ), and Randomized Quasi-Monte Carlo (RQMC). However, when designing a numerical quadrature method for most of the existing Fourier pricing approaches, two key factors affecting the complexity should be carefully controlled, (i) the choice of the vector of damping parameters that ensure the Fourier-integrability and control the regularity class of the integrand, (ii) the high-dimensionality of the integration problem. To address these challenges, in the first part of this thesis we propose a rule for choosing the damping parameters, resulting in smoother integrands. Moreover, we explore the effect of sparsification and dimension-adaptivity in alleviating the curse of dimensionality. Despite the efficiency of ASGQ, the error estimates are very hard to compute. In cases where error quantification is of high priority, in the second part of this thesis, we design an RQMC-based method for the (inverse) Fourier integral computation. RQMC integration is known to be highly efficient for high-dimensional integration problems of sufficiently regular integrands, and it further allows for computation of probabilistic estimates. Nonetheless, using RQMC requires an appropriate domain transformation of the unbounded integration domain to the hypercube, which may originate in a transformed integrand with singularities at the boundaries, and consequently deteriorate the rate of convergence. To preserve the nice properties of the transformed integrand,we propose a model-dependent domain transformation to avoid these corner singularities and retain the optimal efficiency of RQMC. The effectiveness of the proposed optimal damping rule, the designed domain transformation procedure, and their combination with ASGQ and RQMC are demonstrated via several numerical experiments and computational comparisons to the MC approach and the COS method.

<p dir="ltr">This thesis presents applications of one-point quadrature domains to encryption and decryption as well as a method for estimating average temperature. In addition, it investigates methods for finding explicit formulas for certain functions and introduces results regarding quadrature domains for harmonic functions and for double quadrature domains. We use properties of quadrature domains to encrypt and decrypt locations in two dimensions. Results by Bell, Gustafsson, and Sylvan are used to encrypt a planar location as a point in a quadrature domain. A decryption method using properties of quadrature domains is then presented to uncover the location. We further demonstrate how to use data from the decryption algorithm to find an explicit formula for the Schwarz function for a one-point area quadrature domain. Given a double quadrature domain, we show that the fixed points within the area and arc length quadrature identities must be the same, but that the orders at each point may differ between these identities. In the realm of harmonic functions, we demonstrate how to uncover a one-point quadrature identity for harmonic functions from the quadrature identity for a simply-connected one-point quadrature domain for holomorphic functions. We use this result to state theorems for the density of one-point quadrature domains for harmonic functions in the realm of smooth domains with $C^{\infty}$-smooth boundary. These density theorems then lead us to discuss applications of quadrature domains for harmonic functions to estimating average temperature. We end by illustrating examples of the encryption process and discussing the building blocks for future work.</p>

This thesis develops theoretical and computational methods for the robustness analysis of uncertain systems. The considered systems are linearized and depend rationally on random parameters with an associated probability distribution. The uncertainty is tackled by applying a polynomial chaos expansion (PCE), a series expansion for random variables similar to the well-known Fourier series for periodic time signals. We consider the linear perturbations around a system's operating point, i.e., reference trajectory, both from a probabilistic and worst-case point of view. A chief contribution is the polynomial chaos series expansion of uncertain linear systems in linear fractional representation (LFR). This leads to significant computational benefits when analyzing the probabilistic perturbations around a system's reference trajectory. The series expansion of uncertain interconnections in LFR further delivers important theoretical insights. For instance, it is shown that the PCE of rational parameter-dependent linear systems in LFR is equivalent to applying Gaussian quadrature for numerical integration. We further approximate the worst-case performance of uncertain linear systems with respect to quadratic performance metrics. This is achieved by approximately solving the underlying parametric Riccati differential equation after applying a polynomial chaos series expansion. The utility of the proposed probabilistic robustness analysis is demonstrated on the example of an industry-sized autolanding system for an Airbus A330 aircraft. Mean and standard deviation of the stochastic perturbations are quantified efficiently by applying a PCE to a linearization of the system along the nominal approach trajectory. Random uncertainty in the aerodynamic coefficients and mass parameters are considered, as well as atmospheric turbulence and static wind shear. The approximate worst-case analysis is compared with Monte Carlo simulations of the complete nonlinear model. The methods proposed throughout the thesis rapidly provide analysis results in good agreement with the Monte Carlo benchmark, at reduced computational cost.