This thesis presents the results of studies on the problem of subharmonic oscillations in nonlinear Paul trap mass spectrometry. The objective of this thesis is to determine whether the subharmonic oscillations of ions in the trap could in any way affect the quality of mass spectrum in resonance ejection experiments. This is accomplished by studying the existence and stability criteria of these oscillations. This study is done for two casesone in which the auxiliary excitation frequency is close to thrice the ion axial secular frequency and other in which it is close to twice the ion axial secular frequency. Initially, the equations describing the ion motion in the presence of auxiliary excitation are derived. The equations describing the ion motion are then brought into a form easily amenable to analysis by techniques of perturbation theory. The necessary background and definitions to understand the basis for the thesis, along with a survey of results obtained in relevant areas in mass spectrometry and nonlinear dynamics is then developed. The first problem is the study of subharmonic oscillations when the auxiliary excitation frequency is in the vicinity of thrice the ion axial secular frequencies taken up. The application of the multiple time scales technique to the equations describing ion motion gives the slow flow equations, that describe the evolution of amplitudes of axial and radial oscillations. The expression for the steady state amplitudes of these oscillations are then derived. From these expressions the conditions for the existence of the oscillations are obtained in terms of the auxiliary amplitude and the frequency detuning. This is then followed by a detailed stability analysis for the subharmonic oscillation with a given amplitude and phase. The study ends with the discussion of the results obtained, the pertinent numerical studies and the relevance of this study to mass spectrometry. The second study is regarding the problem of subharmonic oscillations when the auxiliary excitation frequency is close to twice the ion axial secular frequency is analyzed. When PoincareLindstedt’s method is applied to the ion motion equations, the amplitude frequency relationship that describes the relation between the steady state subharmonic oscillation amplitude and the frequency detuning is obtained. The variation of the oscillation amplitude with the frequency detuning is then studied. Then follows the analysis of stability. The stability of subharmonic oscillation is analyzed using the results from the standard analysis of Hill’s equation of fourth order. This study ends with the discussion of the results obtained in the context of mass spectrometry. Finally, a summary of the results obtained is discussed.

Dans le cadre du traitement statistique du signal, la plupart des algorithmes couramment utilisés reposent sur l'utilisation de la matrice de covariance des signaux étudiés. En pratique, ce sont les versions adaptatives de ces traitements, obtenues en estimant la matrice de covariance à l'aide d'échantillons du signal, qui sont utilisés. Ces algorithmes présentent un inconvénient : ils peuvent nécessiter un nombre d'échantillons important pour obtenir de bons résultats. Lorsque la matrice de covariance possède une structure rang faible, le signal peut alors être décomposé en deux sous-espaces orthogonaux. Les projecteurs orthogonaux sur chacun de ces sous espaces peuvent alors être construits, permettant de développer des méthodes dites rang faible. Les versions adaptatives de ces méthodes atteignent des performances équivalentes à celles des traitements classiques tout en réduisant significativement le nombre d'échantillons nécessaire. Par ailleurs, l'accroissement de la taille des données ne fait que renforcer l'intérêt de ce type de méthode. Cependant, cet accroissement s'accompagne souvent d'un accroissement du nombre de dimensions du système. Deux types d'approches peuvent être envisagées pour traiter ces données : les méthodes vectorielles et les méthodes tensorielles. Les méthodes vectorielles consistent à mettre les données sous forme de vecteurs pour ensuite appliquer les traitements classiques. Cependant, lors de la mise sous forme de vecteur, la structure des données est perdue ce qui peut entraîner une dégradation des performances et/ou un manque de robustesse. Les méthodes tensorielles permettent d'éviter cet écueil. Dans ce cas, la structure est préservée en mettant les données sous forme de tenseurs, qui peuvent ensuite être traités à l'aide de l'algèbre multilinéaire. Ces méthodes sont plus complexes à utiliser puisqu'elles nécessitent d'adapter les algorithmes classiques à ce nouveau contexte. En particulier, l'extension des méthodes rang faible au cas tensoriel nécessite l'utilisation d'une décomposition tensorielle orthogonale. Le but de cette thèse est de proposer et d'étudier des algorithmes rang faible pour des modèles tensoriels. Les contributions de cette thèse se concentrent autour de trois axes. Un premier aspect concerne le calcul des performances théoriques d'un algorithme MUSIC tensoriel basé sur la Higher Order Singular Value Decomposition (HOSVD) et appliqué à un modèle de sources polarisées. La deuxième partie concerne le développement de filtres rang faible et de détecteurs rang faible dans un contexte tensoriel. Ce travail s'appuie sur une nouvelle définition de tenseur rang faible et sur une nouvelle décomposition tensorielle associée : l'Alternative Unfolding HOSVD (AU-HOSVD). La dernière partie de ce travail illustre l'intérêt de l'approche tensorielle basée sur l'AU-HOSVD, en appliquant ces algorithmes à configuration radar particulière: le Traitement Spatio-Temporel Adaptatif ou Space-Time Adaptive Process (STAP). / Most of statistical signal processing algorithms, are based on the use of signal covariance matrix. In practical cases this matrix is unknown and is estimated from samples. The adaptive versions of the algorithms can then be applied, replacing the actual covariance matrix by its estimate. These algorithms present a major drawback: they require a large number of samples in order to obtain good results. If the covariance matrix is low-rank structured, its eigenbasis may be separated in two orthogonal subspaces. Thanks to the LR approximation, orthogonal projectors onto theses subspaces may be used instead of the noise CM in processes, leading to low-rank algorithms. The adaptive versions of these algorithms achieve similar performance to classic classic ones with less samples. Furthermore, the current increase in the size of the data strengthens the relevance of this type of method. However, this increase may often be associated with an increase of the dimension of the system, leading to multidimensional samples. Such multidimensional data may be processed by two approaches: the vectorial one and the tensorial one. The vectorial approach consists in unfolding the data into vectors and applying the traditional algorithms. These operations are not lossless since they involve a loss of structure. Several issues may arise from this loss: decrease of performance and/or lack of robustness. The tensorial approach relies on multilinear algebra, which provides a good framework to exploit these data and preserve their structure information. In this context, data are represented as multidimensional arrays called tensor. Nevertheless, generalizing vectorial-based algorithms to the multilinear algebra framework is not a trivial task. In particular, the extension of low-rank algorithm to tensor context implies to choose a tensor decomposition in order to estimate the signal and noise subspaces. The purpose of this thesis is to derive and study tensor low-rank algorithms. This work is divided into three parts. The first part deals with the derivation of theoretical performance of a tensor MUSIC algorithm based on Higher Order Singular Value Decomposition (HOSVD) and its application to a polarized source model. The second part concerns the derivation of tensor low-rank filters and detectors in a general low-rank tensor context. This work is based on a new definition of tensor rank and a new orthogonal tensor decomposition : the Alternative Unfolding HOSVD (AU-HOSVD). In the last part, these algorithms are applied to a particular radar configuration : the Space-Time Adaptive Process (STAP). This application illustrates the interest of tensor approach and algorithms based on AU-HOSVD.

This doctoral thesis is the result of a research effort performed in two fields of speech technology, i.e., speech recognition and mispronunciation detection. Although the two areas are clearly distinguishable, the proposed approaches share a common hypothesis based on psychoacoustic processing of speech signals. The conjecture implies that the human auditory periphery provides a relatively good separation of different sound classes. Hence, it is possible to use recent findings from psychoacoustic perception together with mathematical and computational tools to model the auditory sensitivities to small speech signal changes. The performance of an automatic speech recognition system strongly depends on the representation used for the front-end. If the extracted features do not include all relevant information, the performance of the classification stage is inherently suboptimal. The work described in Papers A, B and C is motivated by the fact that humans perform better at speech recognition than machines, particularly for noisy environments. The goal is to make use of knowledge of human perception in the selection and optimization of speech features for speech recognition. These papers show that maximizing the similarity of the Euclidean geometry of the features to the geometry of the perceptual domain is a powerful tool to select or optimize features. Experiments with a practical speech recognizer confirm the validity of the principle. It is also shown an approach to improve mel frequency cepstrum coefficients (MFCCs) through offline optimization. The method has three advantages: i) it is computationally inexpensive, ii) it does not use the auditory model directly, thus avoiding its computational cost, and iii) importantly, it provides better recognition performance than traditional MFCCs for both clean and noisy conditions. The second task concerns automatic pronunciation error detection. The research, described in Papers D, E and F, is motivated by the observation that almost all native speakers perceive, relatively easily, the acoustic characteristics of their own language when it is produced by speakers of the language. Small variations within a phoneme category, sometimes different for various phonemes, do not change significantly the perception of the language’s own sounds. Several methods are introduced based on similarity measures of the Euclidean space spanned by the acoustic representations of the speech signal and the Euclidean space spanned by an auditory model output, to identify the problematic phonemes for a given speaker. The methods are tested for groups of speakers from different languages and evaluated according to a theoretical linguistic study showing that they can capture many of the problematic phonemes that speakers from each language mispronounce. Finally, a listening test on the same dataset verifies the validity of these methods. / <p>QC 20120914</p> / European Union FP6-034362 research project ACORNS / Computer-Animated language Teachers (CALATea)

Active queue management (AQM) techniques for congestion control in Internet Protocol (IP) networks have been designed using both heuristic and analytical methods. But so far, there has been found no AQM scheme designed in the realm of stochastic optimization. Of the many options available in this arena, the gradient-based stochastic approximation method using Infintesimal Perturbation Analysis (IPA) gradient estimators within the Stochastic Fluid Model (SFM) framework is very promising. The research outlined in this thesis provides the theoretical basis and foundational layer for the development of IPA-based AQM schemes. Algorithms for computing the IPA gradient estimators for loss volume and queue workload were derived for the following cases: a single-stage queue with instantaneous, additive loss-feedback, a single-stage queue with instantaneous, additive loss-feedback and an unresponsive competing flow, a single-stage queue with delayed, additive loss-feedback, and a multi-stage tandem network of $m$ queues with instantaneous, additive loss-feedback. For all cases, the IPA gradient estimators were derived with the control parameter, $ heta$, being the buffer-limits of the queue(s). For the single-stage case and the multi-stage case with instantaneous, additive loss-feedback, the IPA gradient estimators for when the control parameter, $ heta$, is the loss-feedback constant, were also derived. Sensitivity analyses and optimizations were performed with control parameter, $ heta$, being the buffer-limits of the queue(s), as well as the loss-feedback constant.

Population projection matrix (PPM) models are a central tool in ecology and evolution. They are widely used for devising population management practises for conservation, pest control, and harvesting. They are frequently employed in comparative analyses that seek to explain demographic patterns in natural populations. They are also a key tool in calculating measures of fitness for evolutionary studies. Yet, demographic analyses using projection matrices have, in some ways, failed to keep up with prevailing ecological paradigms. A common focus on long-term and equilibrium dynamics when analysing projection matrix models fits better with the outmoded view of ecosystems as stable and immutable. The more current view of ecosystems as dynamic and subject to constant extrinsic disturbances has bred new theoretical advances in the study of short-term &quot;transient&quot; dynamics. Transient dynamics can be very different to long-term trends, and given that ecological studies are often conducted over short timescales, they may be more relevant to research. This thesis focuses on the study of transient dynamics using population projection matrix models. The first section presents theoretical, methodological and computational advances in the study of transient dynamics. These are designed to enhance the predictive power of models, whilst keeping data requirements to a minimum, and borrow from the fields of engineering and systems control. Case studies in this section provide support for consideration of transient dynamics in population management. The second section applies some of these new methods to answer pertinent questions surrounding the ecology and evolution of transient dynamics in plants. Results show that transient dynamics exhibit patterns according to life form and phylogenetic history. Evidence suggests that this can be linked to the stage-structuring of life cycles, which opens up the possibility for new avenues of research considering the evolution of transient dynamics in nature.

In this research, an attempt is made to evaluate alternative model-predictive microgrid control approaches and to understand the trade-offs that emerge between model complexity and the ability to achieve real-time optimized system performance. Three alternative controllers are considered and their computational and optimization performance compared. In the first, nonlinearities of the generators are included within the optimization. Subsequently, an approach is considered wherein alternative (non-traditional) states and inputs of generators are used which enables one to leverage linear models with the model predictive control (MPC). Nonlinearities are represented outside the control in maps between MPC inputs and the physical inputs. Third, a recently proposed linearized trajectory (LTMPC) is considered. Finally, the performance of the controllers is examined utilizing alternative models of the synchronous machine that have been proposed for power system analysis.

No description available.

Diese Arbeit beschäftigt sich mit verschiedenen mathematischen Fragestellungen hinsichtlich der Modellierung, Analysis und numerischen Simulation von Gasnetzen. Hierbei liegt der Fokus auf der mathematischen Handhabung von partiellen differential-algebraischen Gleichungen, die mit algebraischen Gleichungen gekoppelt sind. Diese bieten einen einfachen Zugang hinsichtlich der Modellierung von dynamischen Strukturen auf Netzen Somit sind sie insbesondere für Gasnetze geeignet, denen im Zuge der steigenden Bedeutung von erneuerbaren Energien ein gestiegenes Interesse seitens der Öffentlichkeit, Politik und Wissenschaft entgegen gebracht wird. Wir führen zunächst die gängigsten Elemente, die in Gasnetzen benötigt werden ein und formulieren zwei PDAE-Klassen für solche Netze: Eine für reine Rohrnetze, und eine, die zusätzliche Elemente wie Verdichter und Widerstände beinhaltet. Des Weiteren untersuchen wir die Sensitivität der Lösung der Rohrnetz-PDAE hinsichtlich Störungen. Dabei berücksichtigen wir Störungen, die nicht nur den dynamischen Teil der PDAE beeinflussen, sondern auch Störungen in den algebraischen Gleichungen und weisen Stabilitätseigenschaften für die Lösung der PDAE nach. Darüber hinaus beschäftigen wir uns mit einer neu entwickelten, an die Netztopologie angepassten Ortsdiskretisierung, welche die Stabilitätseigenschaften der PDAE auf DAE Systeme überträgt. Des Weiteren zeigen wir, wie sich die Gasnetz-DAE zu einer gewöhnlichen Differentialgleichung, welche die inhärente Dynamik der DAE widerspiegelt entkoppeln lässt. Dieses entkoppelte System kann darüber hinaus direkt aus den Topologie- und Elementinformationen des Netzes aufgestellt werden. Abschließend demonstrieren wir die Ergebnisse an Benchmark-Gasnetzen. Dabei vergleichen wir sowohl die entkoppelte Differentialgleichung mit dem ursprünglichen DAE System, zeigen aber auch, welche Vorteile die an die Netztopologie angepasste Ortsdiskretisierung gegenüber existierenden Verfahren besitzt. / This thesis addresses several aspects regarding modelling, analysis and numerical simulation of gas networks. Hereby, our focus lies on (partial) differential-algebraic equations, thus systems of partial and ordinary differential equations which are coupled by algebraic equations. These coupled systems allow an easy approach towards the modelling of dynamic structures on networks. Therefore, they are well suited for gas networks, which have gained a rise of attention in society, politics and science due to the focus towards renewable energies. We give an introduction towards gas network modelling that includes the most common elements that also appear in real gas networks and present two PDAE systems: One for pipe networks and one that includes additional elements like resistors and compressors. Furthermore, we investigate the impact of perturbations onto the pipe network PDAE, where we explicitly allow perturbations to affect the system in the differential as well as in the algebraic components. We conclude that the solution of the PDAE possesses stability properties. In addition, this thesis introduces a new spatial discretisation that is adapted to the net- work topology. This topology-adapted semi-discretisation results in a DAE which possesses the same perturbation behaviour as the space continuous PDAE. Furthermore, we present a topology based decoupling procedure that allows to reformulate the DAE as an ordinary differential equation (ODE), which represents the inherent dynamics of the DAE system. This ODE, together with a decoupled set of algebraic equations, can be derived from the topology and element information directly. We conclude by demonstrating the established results for several benchmark networks. This includes a comparison of numerical solutions for the decoupled ODE and the DAE system. In addition we present the advantages of the topology-adapted spatial discretisation over existing well established methods.

This thesis presents a mathematical model of the nanoporous anode within a dyesensitised solar cell (DSC). The main purpose of this work is to investigate interfacial charge transfer and charge transport within the porous anode of the DSC under both illuminated and non-illuminated conditions. Within the porous anode we consider many of the charge transfer reactions associated with the electrolyte species, adsorbed dye molecules and semiconductor electrons at the semiconductor-dye- electrolyte interface. Each reaction at this interface is modelled explicitly via an electrochemical equation, resulting in an interfacial model that consists of a coupled system of non-linear algebraic equations. We develop a general model framework for charge transfer at the semiconductor-dye-electrolyte interface and simplify this framework to produce a model based on the available interfacial kinetic data. We account for the charge transport mechanisms within the porous semiconductor and the electrolyte filled pores that constitute the anode of the DSC, through a one- dimensional model developed under steady-state conditions. The governing transport equations account for the diffusion and migration of charge species within the porous anode. The transport model consists of a coupled system of non-linear differential equations, and is coupled to the interfacial model via reaction terms within the mass-flux balance equations. An equivalent circuit model is developed to account for those components of the DSC not explicitly included in the mathematical model of the anode. To obtain solutions for our DSC mathematical model we develop code in FORTRAN for the numerical simulation of the governing equations. We additionally employ regular perturbation analysis to obtain analytic approximations to the solutions of the interfacial charge transfer model. These approximations facilitate a reduction in computation time for the coupled mathematical model with no significant loss of accuracy. To obtain predictions of the current generated by the cell we source kinetic and transport parameter values from the literature and from experimental measurements associated with the DSC commissioned for this study. The model solutions we obtain with these values correspond very favourably with experimental data measured from standard DSC configurations consisting of titanium dioxide porous films with iodide/triiodide redox couples within the electrolyte. The mathematical model within this thesis enables thorough investigation of the interfacial reactions and charge transport within the DSC.We investigate the effects of modified cell configurations on the efficiency of the cell by varying associated parameter values in our model. We find, given our model and the DSC configuration investigated, that the efficiency of the DSC is improved with increasing electron diffusion, decreasing internal resistances and with decreasing dark current. We conclude that transport within the electrolyte, as described by the model, appears to have no limiting effect on the current predicted by the model until large positive voltages. Additionally, we observe that the ultrafast injection from the excited dye molecules limits the interfacial reactions that affect the DSC current.