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Asymptotic Expansions for Second-Order Moments of Integral Functionals of Weakly Correlated Random FunctionsScheidt, Jrgen vom, Starkloff, Hans-Jrg, Wunderlich, Ralf 30 October 1998 (has links)
In the paper asymptotic expansions for
second-order moments of integral functionals
of a class of random functions are considered.
The random functions are assumed to be
$\epsilon$-correlated, i.e. the values are not
correlated excluding a $\epsilon$-neighbourhood
of each point. The asymptotic expansions are
derived for $\epsilon \to 0$. With the help of
a special weak assumption there are found
easier expansions as in the case of general
weakly correlated functions.
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Statistical analysis of networks and biophysical systems of complex architectureValba, Olga 15 October 2013 (has links) (PDF)
Complex organization is found in many biological systems. For example, biopolymers could possess very hierarchic structure, which provides their functional peculiarity. Understating such, complex organization allows describing biological phenomena and predicting molecule functions. Besides, we can try to characterize the specific phenomenon by some probabilistic quantities (variances, means, etc), assuming the primary biopolymer structure to be randomly formed according to some statistical distribution. Such a formulation is oriented toward evolutionary problems.Artificially constructed biological network is another common object of statistical physics with rich functional properties. A behavior of cells is a consequence of complex interactions between its numerous components, such as DNA, RNA, proteins and small molecules. Cells use signaling pathways and regulatory mechanisms to coordinate multiple processes, allowing them to respond and to adapt to changing environment. Recent theoretical advances allow us to describe cellular network structure using graph concepts to reveal the principal organizational features shared with numerous non-biological networks.The aim of this thesis is to develop bunch of methods for studying statistical and dynamic objects of complex architecture and, in particular, scale-free structures, which have no characteristic spatial and/or time scale. For such systems, the use of standard mathematical methods, relying on the average behavior of the whole system, is often incorrect or useless, while a detailed many-body description is almost hopeless because of the combinatorial complexity of the problem. Here we focus on two problems.The first part addresses to statistical analysis of random biopolymers. Apart from the evolutionary context, our studies cover more general problems of planar topology appeared in description of various systems, ranging from gauge theory to biophysics. We investigate analytically and numerically a phase transition of a generic planar matching problem, from the regime, where almost all the vertices are paired, to the situation, where a finite fraction of them remains unmatched.The second part of this work focus on statistical properties of networks. We demonstrate the possibility to define co-expression gene clusters within a network context from their specific motif distribution signatures. We also show how a method based on the shortest path function (SPF) can be applied to gene interactions sub-networks of co-expression gene clusters, to efficiently predict novel regulatory transcription factors (TFs). The biological significance of this method by applying it on groups of genes with a shared regulatory locus, found by genetic genomics, is presented. Finally, we discuss formation of stable patters of motifs in networks under selective evolution in context of creation of islands of "superfamilies".
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Simulation of Weakly Correlated Functions and its Application to Random Surfaces and Random PolynomialsFellenberg, Benno, Scheidt, Jürgen vom, Richter, Matthias 30 October 1998 (has links)
The paper is dedicated to the modeling and the
simulation of random processes and fields.
Using the concept and the theory of weakly
correlated functions a consistent representation
of sufficiently smooth random processes
will be derived. Special applications will be
given with respect to the simulation of road
surfaces in vehicle dynamics and to the
confirmation of theoretical results with
respect to the zeros of random polynomials.
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[en] ARITHMETIC STRUCTURES IN RANDOM SETS / [pt] ESTRUTURAS ARITMÉTICAS EM CONJUNTOS ALEATÓRIOSMATHEUS SECCO TORRES DA SILVA 08 September 2020 (has links)
[pt] Nesta tese de Doutorado, nós estudamos cotas para as probabilidades de desvio de uma variável aleatória X que conta o número de arestas de um hipergrafo induzido por um subconjunto aleatório de m elementos do seu conjunto de vértices. Nós consideramos dois contextos: o primeiro corresponde a hipergrafos que possuem certo tipo de regularidade, ao passo que o segundo lida com hipergrafos que são, em algum sentido, longe de serem regulares. É possível aplicar estes resultados a estruturas discretas, como o conjunto de progressões aritméticas de tamanho k no grupo aditivo de inteiros módulo um primo e também no conjunto dos N primeiros inteiros positivos. Além disso, também deduzimos resultados para o caso em que o subconjunto aleatório é gerado incluindo cada vértice do hipergrafo independentemente com probabilidade p. / [en] In this Ph.D. thesis, we study bounds for the deviation probabilities of a random variable X that counts the number of edges of a hypergraph induced by a random m–element subset of its vertex set. We consider two contexts: the first corresponds to hypergraphs with some kind of regularity, whereas the second addresses hypergraphs that are in some sense far from being regular. It is possible to apply these results to discrete structures such as the set of k–term arithmetic progressions in the additive group of integers modulo a prime and in the set of the first N positive integers. Furthermore, we also deduce results for the case when the random subset is generated by including each vertex of the hypergraph independently with probability p.
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[pt] O MÉTODO DE EQUAÇÕES DIFERENCIAIS E CONJUNTOS INDEPENDENTES EM HIPERGRAFOS / [en] THE DIFFERENTIAL EQUATIONS METHOD AND INDEPENDENT SETS IN HYPERGRAPHSIGOR ALBUQUERQUE ARAUJO 18 September 2019 (has links)
[pt] Nesta dissertação, discutiremos o método de equações diferenciais de Wormald, que possui muitas aplicações recentes em Combinatória. Esse método explora a interação entre a matemática discreta e contínua e pode ser usado para provar concentração em uma grande quantidade de processos aleatórios discretos. Em particular, estudaremos o processo livre de H e o algoritmo guloso aleatório para gerar conjuntos independentes em hipergrafos. Esses processos tem sido amplamente estudados nos últimos
anos, culminando com o recente grande avanço de Tom Bohman e Patrick Bennett em 2016, que obtiveram uma cota inferior para hipergrafos com certas condições de densidade. Nós não só reproduzimos sua demonstração mas também obtemos um resultado mais forte (expandindo seu resultado para hipergrafos mais esparsos) e analisamos o caso de hipergrafos lineares, com o intuito de progredir rumo a uma conjectura de Johnson e Pinto sobre o processo livre de Q2 no hipercubo Qd. / [en] In this dissertation, we will discuss Wormald s differential equations method, which has recently had many intriguing applications in Combinatorics. This method explores the interplay between discrete and continuous mathematics and it can be used to prove concentration in a number of discrete random processes. In particular, we will discuss the H-free process and the random greedy algorithm to obtain independent sets in hypergraphs. These processes had been extensively studied through the past few years, culminating in the recent breakthrough of Tom Bohman and Patrick Bennett in 2016, who obtained a lower bound for hypergraphs with certain density conditions. We not only reproduce the proof given by them but also obtain a stronger result (expanding their result to sparser hypergraphs) and we analyze the case of linear hypergraphs, in order to make progress towards a conjecture by Johnson and Pinto concerning the Q2-free process in the hypercube Qd.
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Statistical analysis of networks and biophysical systems of complex architecture / L'analyse statistique des réseaux et des systèmes biophysiques de l'architecture complexeValba, Olga 15 October 2013 (has links)
De nombreux systèmes biologiques présentent une organisation complexe. Par exemple, les biopolymères peuvent posséder une structure très hiérarchisée responsable de leur fonction particulière. Comprendre la complexité de cette organisation permet de décrire des phénomènes biologiques et de prédire les fonctions des molécules. En outre, en supposant que la structure primaire du polymère est formée aléatoirement, nous pouvons essayer de caractériser ce phénomène par des grandeurs probabilistes (variances, moyennes, etc). Cette formulation est propre aux problèmes d'évolution.Les réseaux biologiques sont d'autres objets communs de la physique statistique possédant de riches propriétés fonctionnelles. Pour décrire un mécanisme biologique, on utilise différents types de réseaux biomoléculaires. Le développement de nouvelles approches peut nous aider à structurer, représenter et interpréter des données expérimentales, comprendre les processus cellulaires et prédire la fonction d'une molécule.L'objectif de cette thèse est de développer des méthodes pour l'étude d'objets statiques ou dynamiques, ayant une architecture complexe. Ici, nous nous intéressons à deux problèmes.La première partie est consacrée à l'analyse statistique des biopolymères aléatoires. Nous étudions une transition de phase présente dans les séquences aléatoires de l'ARN. On met alors en évidence deux modes : le régime où presque toutes les bases qui composent l'ARN sont couplées et la situation où une fraction finie de ces bases restent non complémentaires.La deuxième partie de cette thèse se concentre sur les propriétés statistiques des réseaux. Nous développons des méthodes pour l'identification d'amas de gènes co-expressifs sur les réseaux et la prédiction de gènes régulateurs novateurs. Pour cela, nous utilisons la fonction du plus court chemin et l'analyse du profil des motifs formés par ces amas. Ces méthodes ont pu prédire les facteurs de transcription impliqués dans le processus de longévité. Enfin, nous discutons de la formation de motifs stables sur les réseaux due à une évolution sélective. / Complex organization is found in many biological systems. For example, biopolymers could possess very hierarchic structure, which provides their functional peculiarity. Understating such, complex organization allows describing biological phenomena and predicting molecule functions. Besides, we can try to characterize the specific phenomenon by some probabilistic quantities (variances, means, etc), assuming the primary biopolymer structure to be randomly formed according to some statistical distribution. Such a formulation is oriented toward evolutionary problems.Artificially constructed biological network is another common object of statistical physics with rich functional properties. A behavior of cells is a consequence of complex interactions between its numerous components, such as DNA, RNA, proteins and small molecules. Cells use signaling pathways and regulatory mechanisms to coordinate multiple processes, allowing them to respond and to adapt to changing environment. Recent theoretical advances allow us to describe cellular network structure using graph concepts to reveal the principal organizational features shared with numerous non-biological networks.The aim of this thesis is to develop bunch of methods for studying statistical and dynamic objects of complex architecture and, in particular, scale-free structures, which have no characteristic spatial and/or time scale. For such systems, the use of standard mathematical methods, relying on the average behavior of the whole system, is often incorrect or useless, while a detailed many-body description is almost hopeless because of the combinatorial complexity of the problem. Here we focus on two problems.The first part addresses to statistical analysis of random biopolymers. Apart from the evolutionary context, our studies cover more general problems of planar topology appeared in description of various systems, ranging from gauge theory to biophysics. We investigate analytically and numerically a phase transition of a generic planar matching problem, from the regime, where almost all the vertices are paired, to the situation, where a finite fraction of them remains unmatched.The second part of this work focus on statistical properties of networks. We demonstrate the possibility to define co-expression gene clusters within a network context from their specific motif distribution signatures. We also show how a method based on the shortest path function (SPF) can be applied to gene interactions sub-networks of co-expression gene clusters, to efficiently predict novel regulatory transcription factors (TFs). The biological significance of this method by applying it on groups of genes with a shared regulatory locus, found by genetic genomics, is presented. Finally, we discuss formation of stable patters of motifs in networks under selective evolution in context of creation of islands of "superfamilies".
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Topological Optimization in Network Dynamical Systems / Topologieoptimierung in Netzwerke Dynamische SystemeVan Bussel, Frank 25 August 2010 (has links)
No description available.
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Etudes expérimentales et numériques des instabilités non-linéaires et des vagues scélérates optiques / Experimental and numerical studies of nonlinear instabilities and optical rogue wavesWetzel, Benjamin 06 December 2012 (has links)
Ces travaux de thèse rapportent l’étude des instabilités non-linéaires et des évènements extrêmesse développant lors de la propagation guidée d’un champ électromagnétique au sein de fibresoptiques. Après un succinct rappel des divers processus linéaires et non-linéaires menant à lagénération de super continuum optique, nous montrons que le spectre de celui-ci peut présenterde larges fluctuations, incluant la formation d’événements extrêmes, dont les propriétés statistiqueset l’analogie avec les vagues scélérates hydrodynamiques sont abordées en détail. Nous présentonsune preuve de principe de l’application de ces fluctuations spectrales à la génération de nombres etde marches aléatoires et identifions le phénomène d’instabilité de modulation, ayant lieu lors de laphase initiale d’expansion spectrale du super continuum, comme principale contribution à la formationd’événements extrêmes. Ce mécanisme est étudié numériquement et analytiquement, en considérantune catégorie de solutions exactes de l’équation de Schrödinger non-linéaire présentant descaractéristiques de localisations singulières. Les résultats obtenus sont vérifiés expérimentalement,notamment grâce à un système de caractérisation spectrale en temps réel et à l’utilisation conjointede métriques statistiques innovantes (ex : cartographie de corrélations spectrales). L’excellent accordentre simulations et expériences a permis de valider les prédictions théoriques et d’accéder àune meilleure compréhension des dynamiques complexes inhérentes à la propagation non-linéaired’impulsions optiques. / This thesis reports the study of nonlinear instabilities and extreme events occurring during the guidedpropagation of an electromagnetic field into optical fibers. After a short overview of the various linearand nonlinear processes leading to optical supercontinuum generation, we show that its spectrumcan exhibit large fluctuations, including the formation of extreme events, whose statistical propertiesas well as hydrodynamic rogue waves analogy are studied in detail. We provide a proof of principle ofusing these spectral fluctuations for random number and random walk generation and identify modulationinstability, associated with the onset phase of supercontinuum spectral broadening, as themain phenomenon leading to extreme event formation. This mechanism is studied both numericallyand analytically, considering a class of exact solutions of nonlinear Schrödinger equation which exhibitsingular localization characteristics. The results are experimentally verified, especially througha real-time spectral characterization system along with the use of innovative statistical metrics (e.g.spectral correlation maps). The excellent agreement between simulations and experiments allowedus to validate the theoretical predictions and get further insight into the complex dynamics associatedto nonlinear optical pulse propagation.
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Estimation Problems Related to Random Matrix Ensembles / Schätzprobleme für Ensembles zufälliger MatrizenMatić, Rada 06 July 2006 (has links)
No description available.
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Méthodologie d’analyse des signaux et caractérisation hydrogéologique : application aux chroniques de données obtenues aux laboratoires souterrains du Mont Terri, Tournemire et Meuse/Haute-Marne / Signal analyzis methodology and hydrogeologic characterization : application to time series collected at the underground research laboratories of Mont Terri, Tournemire, and Meuse/Haute-MarneFatmi, Hassane 29 May 2009 (has links)
Ce rapport présente des méthodes de prétraitement, d'analyse statistique et d'interprétation de chroniques hydrogéologiques de massifs peu perméables (argilites) dans le cadre d'études sur le stockage profond de déchets radioactifs. Les séries temporelles analysées sont la pression interstitielle et la pression atmosphérique, en relation avec différents phénomènes (marées terrestres, effet barométrique, évolution de l'excavation des galeries). Les pré-traitements permettent de reconstituer et homogénéiser les chroniques de données en présence de lacunes, aberrations, et pas de temps variables. Les signaux prétraités sont ensuite analysés en vue de caractériser les propriétés hydrauliques du massif peu perméable (emmagasinement spécifique ; porosité effective). Pour cela, on a développé et mis en oeuvre les méthodes d'analyses suivantes (implémentées en Matlab): analyses corrélatoires et spectrales (Fourier) ; analyses ondelettes multirésolution ; enveloppes de signaux aléatoires. Cette méthodologie est appliquée aux données acquises au Laboratoire Souterrain du Consortium International du Mont Terri (Jura Suisse), ainsi qu'à certaines données des Laboratoires Souterrains de Tournemire (Aveyron) et de Meuse / Haute-Marne (ANDRA) / This report presents a set of statistical methods for pre-processing and analyzing multivariate hydrogeologic time series, such as pore pressure and its relation to atmospheric pressure. The goal is to study the hydrogeologic characteristics of low permeability geologic formations (argilite) in the context of deep disposal of radioactive waste. The pressure time series are analyzed in relation with different phenomena, such as earth tides, barometric effects, and the evolution of excavated galleries. The pre-processing is necessary for reconstituting and homogenizing the time series in the presence of data gaps, outliers, and variable time steps. The preprocessed signals are then analyzed with a view to characterizing the hydraulic properties of this type of low permeability formation (specific storativity; effective porosity). For this sake, we have developed and used the following methods (implemented in Matlab): temporal correlation analyses; spectral/Fourier analyses; multiresolution wavelet analyses envelopes of random processes. This methodology is applied to data collected at the URL (Underground Research Laboratory) of the Mont Terri International Consortium (Swiss Jura), as well as some other data collected at the URL of IRSN at Tournemire (Aveyron) and at the URL of ANDRA (Meuse / Haute-Marne)
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