Hybrid systems with or without stochastic noise and with or without time delay are addressed and the qualitative properties of these systems are investigated. The main contribution of this thesis is distributed in three parts. In Part I, nonlinear stochastic impulsive systems with time delay (SISD) with variable impulses are formulated and some of the fundamental properties of the systems, such as existence of local and global solution, uniqueness, and forward continuation of the solution are established. After that, stability and input-to-state stability (ISS) properties of SISD with fixed impulses are developed, where Razumikhin methodology is used. These results are then carried over to discussed the same qualitative properties of large scale SISD. Applications to automated control systems and control systems with faulty actuators are used to justify the proposed approaches. Part II is devoted to address ISS of stochastic ordinary and delay switched systems. To achieve a variety stability-like results, multiple Lyapunov technique as a tool is applied. Moreover, to organize the switching among the system modes, a newly developed initial-state-dependent dwell-time switching law and Markovian switching are separately employed. Part III deals with systems of differential equations with piecewise constant arguments with and without random noise. These systems are viewed as a special type of hybrid systems. Existence and uniqueness results are first obtained. Then, comparison principles are established which are later applied to develop some stability results of the systems.

This thesis consists of a summary and five papers, dealing with financial applications of optimal stopping, optimal control and volatility. In Paper I, we present a method to recover a time-independent piecewise constant volatility from a finite set of perpetual American put option prices. In Paper II, we study the optimal liquidation problem under the assumption that the asset price follows a geometric Brownian motion with unknown drift, which takes one of two given values. The optimal strategy is to liquidate the first time the asset price falls below a monotonically increasing, continuous time-dependent boundary. In Paper III, we investigate the optimal liquidation problem under the assumption that the asset price follows a jump-diffusion with unknown intensity, which takes one of two given values. The best liquidation strategy is to sell the asset the first time the jump process falls below or goes above a monotone time-dependent boundary. Paper IV treats the optimal dividend problem in a model allowing for positive jumps of the underlying firm value. The optimal dividend strategy is of barrier type, i.e. to pay out all surplus above a certain level as dividends, and then pay nothing as long as the firm value is below this level. Finally, in Paper V it is shown that a necessary and sufficient condition for the explosion of implied volatility near expiry in exponential Lévy models is the existence of jumps towards the strike price in the underlying process.

The mathematical analysis of dynamical systems covers a wide range of challenging problems related to the time evolution, transient and asymptotic behavior, or regulation and control of physical systems. A large part of my work has been motivated by new mathematical questions arising from biological systems, especially signaling and genetic regulatory networks, where the classical methods usually don't directly apply. Problems include parameter estimation, robustness of the system, model reduction, or model assembly from smaller modules, or control of a system towards a desired state. Although many different formalisms and methodologies can be used to study these problems, in the past decade my work has focused on discrete and hybrid modeling frameworks with the goal of developing intuitive, computationally amenable, and mathematically rigorous, methods of analysis. Discrete (and, in particular, Boolean) models involve a high degree of abstraction and provide a qualitative description of the systems' dynamics. Such models are often suitable to represent the known interactions in gene regulatory networks and their advantage is that a large range of theoretical analysis tools are available using, for instance, graph theoretical concepts. Hybrid (piecewise affine) models have discontinuous vector fields but provide a continuous and more quantitative description of the dynamics. These systems can be analytically studied in each region of an appropriate partition of the state space, and the full solution given as a concatenation of the solutions in each region. Here, I will introduce the two formalisms and then, using several examples, illustrate how a combination of different formalisms permits comparison of results, as well as gaining quantitative knowledge and predictive power on a biological system, through the use of complementary mathematical methods.

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Au cours des deux dernières décennies, les signaux chaotiques ont été de plus en plus pris en compte dans les télécommunications, traitement du signal ou transmissions sécurisées. De nombreux articles ont été publiés qui étudient la densité spectrale de puissance (DSP) des signaux générés par des transformations spécifiques. La concentration sur la DSP est due à l'importance de la fréquence dans les télécommunications et la transmission sécurisée. Grâce au grand nombre de systèmes sans fil, la disponibilité des fréquences de transmission et de réception est de plus en plus rare pour les communications sans fil. Aussi, les médias guidés ont des limitations liées à la bande passante du signal. Dans cette thèse, nous étudions certaines propriétés associées à la bifurcation collision de frontière pour une transformation unidimensionnelle linéaire par morceaux avec trois pentes et deux paramètres. Nous calculons les expressions analytiques de l'autocorrélation et de la densité spectrale de puissance des signaux chaotiques générés par les transformations linéaires par morceaux. Nous montrons l'existence d'une forte relation entre les différents types de densité spectrale de puissance (passe-bas, passe-haut ou coupe-bande) et les paramètres de bifurcation. Nous notons également en évidence une relation entre le type de spectre et l'ordre des cycles attractifs. Le type du spectre dépend de l'existence des orbites périodiques au-delà de la bifurcation de collision de frontière qui a donné naissance au chaos. Nous utilisons ensuite les transformations chaotiques pour étudier la fonction d'ambiguïté. Nous combinons quelques transformations chaotiques bien déterminées pour obtenir un spectre large bande avec une bonne fonction d'ambiguïté qui peut être utilisée en système radar.

在迴歸分析中，若變數間具有非線性 (nonlinear) 的關係時，B-Spline線性迴歸是以無母數的方式建立模型。B-Spline函數為具有節點(knots)的分段多項式，選取合適節點的位置對B-Spline函數的估計有重要的影響，在希望得到B-Spline較好的估計量的同時，我們也想要只用少數的節點就達成想要的成效，於是Huang (2013) 提出了一種選擇節點的方式APLS (Adaptive penalized least squares)，在本文中，我們以此方法進行一些更一般化的設定，並在不同的設定之下，判斷是否有較好的估計效果，且已修正後的方法與基於BIC (Bayesian information criterion)的節點估計方式進行比較，在本文中我們將一般化設定的APLS法稱為GAPLS，並且經由模擬結果我們發現此兩種以B-Spline進行迴歸函數近似的方法其近似效果都很不錯，只是節點的個數略有不同，所以若是對節點選取的個數有嚴格要求要取較少的節點的話，我們建議使用基於BIC的節點估計方式，除此之外GAPLS法也是不錯的選擇。 / In regression analysis, if the relationship between the response variable and the explanatory variables is nonlinear, B-splines can be used to model the nonlinear relationship. Knot selection is crucial in B-spline regression. Huang (2013) propose a method for adaptive estimation, where knots are selected based on penalized least squares. This method is abbreviated as APLS (adaptive penalized least squares) in this thesis. In this thesis, a more general version of APLS is proposed, which is abbreviated as GAPLS (generalized APLS). Simulation studies are carried out to compare the estimation performance between GAPLS and a knot selection method based on BIC (Bayesian information criterion). The simulation results show that both methods perform well and fewer knots are selected using the BIC approach than using GAPLS.

Hybrid systems with or without stochastic noise and with or without time delay are addressed and the qualitative properties of these systems are investigated. The main contribution of this thesis is distributed in three parts. In Part I, nonlinear stochastic impulsive systems with time delay (SISD) with variable impulses are formulated and some of the fundamental properties of the systems, such as existence of local and global solution, uniqueness, and forward continuation of the solution are established. After that, stability and input-to-state stability (ISS) properties of SISD with fixed impulses are developed, where Razumikhin methodology is used. These results are then carried over to discussed the same qualitative properties of large scale SISD. Applications to automated control systems and control systems with faulty actuators are used to justify the proposed approaches. Part II is devoted to address ISS of stochastic ordinary and delay switched systems. To achieve a variety stability-like results, multiple Lyapunov technique as a tool is applied. Moreover, to organize the switching among the system modes, a newly developed initial-state-dependent dwell-time switching law and Markovian switching are separately employed. Part III deals with systems of differential equations with piecewise constant arguments with and without random noise. These systems are viewed as a special type of hybrid systems. Existence and uniqueness results are first obtained. Then, comparison principles are established which are later applied to develop some stability results of the systems.

Le but de cette thèse est de développer une méthode numérique simple, robuste, efficace et précise pour résoudre des problèmes d'ingénierie de grande taille à partir de la méthode Taylor Meshless (TMM) et fournir de nouvelles idées principales de TMM est d'utiliser comme fonctions de forme des polynômes d'ordre élevé qui sont des solutions approchées de l'EDP. Ainsi la discrétisation ne concerne que la frontière. Les coefficients de ces fonctions de forme sont obtenus en discrétisant les conditions aux limites par des procédures de collocation associées à la méthode des moindres carrés. TMM est alors une véritable méthode sans maillage sans processus d'intégration, les conditions aux limites étant obtenues par collocation. Les principales contributions de cette thèse sont les suivantes: 1) Basé sur TMM, un algorithme général et efficace a été développé pour résoudre des EDP elliptiques tridimensionnelles; 2) Trois techniques de couplage pour des résolutions par morceaux ont été discutées dans des cas de problèmes à grande échelle: la méthode de collocation par les moindres carrés et deux méthodes de couplage basées sur les multiplicateurs de Lagrange; 3) Une méthode numérique générale pour résoudre les EDP non-linéaires a été proposée en combinant la méthode de Newton, la TMM et la technique de différentiation automatique. 4) Pour résoudre des problèmes avec un bord non régulier, des solutions singulières satisfaisant l'équation de contrôle sont introduites comme des fonctions de forme complémentaires, ce qui fournit une base théorique pour la résolution de problèmes singuliers / Based on Taylor Meshless Method (TMM), the aim of this thesis is to develop a simple, robust, efficient and accurate numerical method which is capable of solving large scale engineering problems and to provide a new idea for the follow-up study on meshless methods. To this end, the influence of the key factors in TMM has been studied by solving three-dimensional and non-linear Partial Differential Equations (PDEs). The main idea of TMM is to use high order polynomials as shape functions which are approximated solutions of the PDE and the discretization concerns only the boundary. To solve the unknown coefficients, boundary conditions are accounted by collocation procedures associated with least-square method. TMM that needs only boundary collocation without integration process, is a true meshless method. The main contributions of this thesis are as following: 1) Based on TMM, a general and efficient algorithm has been developed for solving three-dimensional PDEs; 2) Three coupling techniques in piecewise resolutions have been discussed and tested in cases of large-scale problems, including least-square collocation method and two coupling methods based on Lagrange multipliers; 3) A general numerical method for solving non-linear PDEs has been proposed by combining Newton Method, TMM and Automatic Differentiation technique; 4) To apply TMM for solving problems with singularities, the singular solutions satisfying the control equation are introduced as complementary shape functions, which provides a theoretical basis for solving singular problems

De nombreux travaux récents ont démontré l’importance de la stochasticité dans l’expression des gènes à différentes échelles. On passera tout d’abord en revue les principaux résultats expérimentaux pour motiver l’étude de modèles mathèmatiques prenant en comptedes effets aléatoires. On étudiera ensuite deux modèles particuliers où les effets aléatoires induisent des comportements intéressants, en lien avec des résultats expérimentaux : une dynamique intermittente dans un modèle d’auto-régulation de l’expression d’un gène ; et l’émergence d’hétérogénéité à partir d’une population homogène de protéines par modification post-traductionnelle. Dans le Chapitre I, nous avons étudié le modèle standard d’expression des gènes à trois variables : ADN, ARN messager et protéine. L’ADN peut être dans deux états, respectivement “ON“ et “OFF“. La transcription (production d’ARN messagers) peut avoir lieu uniquement dans l’état “ON“. La traduction (production de protéines) est proportionnelleà la quantité d’ARN messager. Enfin la quantité de protéines peut réguler de manière non-linéaire les taux de production précédent. Nous avons utilisé des théorèmesde convergence de processus stochastique pour mettre en évidence différents régimes de ce modèle. Nous avons ainsi prouvé rigoureusement le phénomène de production intermittente d’ARN messagers et/ou de protéines. Les modèles limites obtenues sont alors des modèles hybrides, déterministes par morceaux avec sauts Markoviens. Nous avons étudié le comportement en temps long de ces modèles et prouvé la convergence vers des solutions stationnaires. Enfin, nous avons étudié en détail un modèle réduit, calculé explicitement la solution stationnaire, et étudié le diagramme de bifurcation des densités stationnaires. Ceci a permis 1) de mettre en évidence l’influence de la stochasticité en comparant aux modèles déterministes ; 2) de donner en retour un moyen théorique d’estimer la fonctionde régulation par un problème inverse. Dans le Chapitre II, nous avons étudié une version probabiliste du modèle d’agrégation fragmentation. Cette version permet une définition de la nucléation en accord avec les modèles biologistes pour les maladies à Prion. Pour étudier la nucléation, nous avons utilisé une version stochastique du modèle de Becker-Dôring. Dans ce modèle, l’agrégation est réversible et se fait uniquement par attachement/détachement d’un monomère. Le temps de nucléation est définit comme le premier temps où un noyau (c’est-à-dire un agrégat de taille fixé, cette taille est un paramètre du mod`ele) est formé. Nous avons alors caractérisé la loi du temps de nucléation dans ce modèle. La distribution de probabilitédu temps de nucléation peut prendre différente forme selon les valeurs de paramètres : exponentielle, bimodale, ou de type Weibull. Concernant le temps moyen de nucléation, nous avons mis en évidence deux phénomènes importants. D’une part, le temps moyen denucl´eation est une fonction non-monotone du paramètre cinétique d’agrégation. D’autre part, selon la valeur des autres paramètres, le temps moyen de nucléation peut dépendre fortement ou très faiblement de la quantité initiale de monomère . Ces caractérisations sont importantes pour 1) expliquer des dépendances très faible en les conditions initiales,observées expérimentalement ; 2) déduire la valeur de certains paramètres d’observations expérimentales. Cette étude peut donc être appliqué à des données biologiques. Enfin, concernant un modèle de polymérisation-fragmentation, nous avons montré un théorème limite d’un modèle purement discret vers un modèle hybride, qui peut-être plus utile pourdes simulations numériques, ainsi que pour une étude théorique. / The importance of stochasticity in gene expression has been widely shown recently. Wewill first review the most important related work to motivate mathematical models thattakes into account stochastic effects. Then, we will study two particular models where stochasticityinduce interesting behavior, in accordance with experimental results : a bursting dynamic in a self-regulating gene expression model ; and the emergence of heterogeneityfrom a homogeneous pool of protein by post-translational modification.In Chapter I, we studied a standard gene expression model, at three variables : DNA, messenger RNA and protein. DNA can be in two distinct states, ”ON“ and ”OFF“. Transcription(production of mRNA) can occur uniquely in the ”ON“ state. Translation (productionof protein) is proportional to the quantity of mRNA. Then, the quantity of proteincan regulate in a non-linear fashion these production rates. We used convergence theoremof stochastic processes to highlight different behavior of this model. Hence, we rigorously proved the bursting phenomena of mRNA and/or protein. Limiting models are then hybridmodel, piecewise deterministic with Markovian jumps. We studied the long time behaviorof these models and proved convergence toward a stationary state. Finally, we studied indetail a reduced model, explicitly calculated the stationary distribution and studied itsbifurcation diagram. Our two main results are 1) to highlight stochastic effects by comparisonwith deterministic model ; 2) To give back a theoretical tool to estimate non-linear regulation function through an inverse problem. In Chapter II, we studied a probabilistic version of an aggregation-fragmentation model. This version allows a definition of nucleation in agreement with biological model for Prion disease. To study the nucleation, we used a stochastic version of the Becker-Döring model. In this model, aggregation is reversible and through attachment/detachment of amonomer. The nucleation time is defined as a waiting time for a nuclei (aggregate of afixed size, this size being a parameter of the model) to be formed. In this work, we characterized the law of the nucleation time. The probability distribution of the nucleation timecan take various forms according parameter values : exponential, bimodal or Weibull. Wealso highlight two important phenomena for the mean nucleation time. Firstly, the mean nucleation time is a non-monotone function of the aggregation kinetic parameter. Secondly, depending of parameter values, the mean nucleation time can be strongly or very weakly correlated with the initial quantity of monomer. These characterizations are important for 1) explaining weak dependence in initial condition observed experimentally ; 2) deducingsome parameter values from experimental observations. Hence, this study can be directly applied to biological data. Finally, concerning a polymerization-fragmentation model, weproved a convergence theorem of a purely discrete model to hybrid model, which may beuseful for numerical simulations as well as a theoretical study.

Submitted by Liliane Ferreira (ljuvencia30@gmail.com) on 2018-06-14T11:12:47Z No. of bitstreams: 2 Tese - João Lopes Cardoso Filho - 2018.pdf: 1729607 bytes, checksum: 8279e98ec23b68bab062f8c812957bf4 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-06-15T10:25:16Z (GMT) No. of bitstreams: 2 Tese - João Lopes Cardoso Filho - 2018.pdf: 1729607 bytes, checksum: 8279e98ec23b68bab062f8c812957bf4 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-06-15T10:25:16Z (GMT). No. of bitstreams: 2 Tese - João Lopes Cardoso Filho - 2018.pdf: 1729607 bytes, checksum: 8279e98ec23b68bab062f8c812957bf4 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-05-18 / Fundação de Amparo à Pesquisa do Estado de Goiás - FAPEG / In this work we exhibit canonical forms for 2D codimension one piecewise smooth vector Fields (PSVF). All possible orientations and codimension one scenarios were covered. Also the intrinsic objects that characterize each one of the canonical forms were presented. Also we present topological distinct canonical forms for a larger class for symmetric PSVF where the set of fixed points is contained in the variety os discontinuity. Finally we analyze the simultaneous occurrence of sliding and crossing limit cycle in the case where the piecewise linear vector fields presents a continuum of periodic orbits. / Neste trabalho exibiremos inicialmente as formas canônicas para campos vetoriais suaves por partes (PSVF) no plano. Todas os possíveis cenários de codimensão um são abordados. Também apresentamos formas canônicas topologicamente distintas para uma classe de PSVF com simetria onde o conjunto de pontos fixos está contido na variedade de descontinuidade. Finalmente, analisaremos a ocorrência simultânea de ciclos limite costurantes e deslizantes no caso linear por partes que apresentam um contínuo de órbitas periódicas.