Shape signifiers for control of a low-order compressor model

Rotating stall and surge, two instability mechanisms limiting the performance of aeroengines compressors, are studied on the third-order Moore-Greitzer model. The skewness of the compressor characteristic, a single parameter shape signifier, is shown to determine the key qualitative properties of feedback control.

Two-dimensional simulation of high-order laterally-coupled GaAs-AlGaAs DFB laser diodes

Laterally-coupled distributed feedback (LC-DFB) laser diodes made without an epitaxial re-growth process have the advantage of a simple fabrication process. In this paper, two-dimensional optical field distribution of the fundamental quasi TE (transverse electric) mode is calculated by means of a semivectorial finite-difference method (SV-FDM). The dependence of the effective coupling coefficient (kappa(eff)) on the dutycycle of first-, second- and third-order LC-DFB LDs is investigated using modified coupled wave equations.

Higher-order effects and ultrashort solitons in left-handed metamaterials

Starting from Maxwell's equations, we use the reductive perturbation method to derive a second-order and a third-order nonlinear Schrodinger equation, describing ultrashort solitons in nonlinear left-handed metamaterials. We find necessary conditions and derive exact bright and dark soliton solutions of these equations for the electric and magnetic field envelopes.

Polynomial Model for High-Order and Multi-Carrier Passive Intermodulation Products

Passive intermodulation (PIM) often limits the performance of communication systems, particularly in the presence of multiple carriers. Since the origins of the apparently multiple physical sources of nonlinearity causing PIM in distributed circuits are not fully understood, the behavioural models are frequently employed to describe the process of PIM generation. In this paper, a memoryless nonlinear polynomial model, capable of predicting high-order multi-carrier intermodulation products, is deduced from the third-order two-tone PIM measurements on a microstrip transmission line with distributed nonlinearity. The analytical model of passive distributed nonlinearity is implemented in Keysight Technology’s ADS simulator to evaluate the adjacent band power ratio for three-tone signals. The obtained results suggest that the costly multi-carrier test setups can possibly be replaced by a simulation tool based on the properly retrieved nonlinear polynomial model.

Quantum criptography in optical fibers

As comunicações quânticas aplicam as leis fundamentais da física quântica para codificar, transmitir, guardar e processar informação. A mais importante e bem-sucedida aplicação é a distribuição de chaves quânticas (QKD). Os sistemas de QKD são suportados por tecnologias capazes de processar fotões únicos. Nesta tese analisamos a geração, transmissão e deteção de fotões únicos e entrelaçados em fibras óticas. É proposta uma fonte de fotões única baseada no processo clássico de mistura de quatro ondas (FWM) em fibras óticas num regime de baixas potências. Implementamos essa fonte no laboratório, e desenvolvemos um modelo teórico capaz de descrever corretamente o processo de geração de fotões únicos. O modelo teórico considera o papel das nãolinearidades da fibra e os efeitos da polarização na geração de fotões através do processo de FWM. Analisamos a estatística da fonte de fotões baseada no processo clássico de FWM em fibras óticas. Derivamos um modelo teórico capaz de descrever a estatística dessa fonte de fotões. Mostramos que a estatística da fonte de fotões evolui de térmica num regime de baixas potências óticas, para Poissoniana num regime de potências óticas moderadas. Validamos experimentalmente o modelo teórico, através do uso de fotodetetores de avalanche, do método estimativo da máxima verossimilhança e do algoritmo de maximização de expectativa. Estudamos o processo espontâneo de FWM como uma fonte condicional de fotões únicos. Analisamos a estatística dessa fonte em termos da função condicional de coerência de segunda ordem, considerando o espalhamento de Raman na geração de pares de fotões, e a perda durante a propagação de fotões numa fibra ótica padrão. Identificamos regimes apropriados onde a fonte é quase ideal. Fontes de pares de fotões implementadas em fibras óticas fornecem uma solução prática ao problema de acoplamento que surge quando os pares de fotões são gerados fora da fibra. Exploramos a geração de pares de fotões através do processo espontâneo de FWM no interior de guias de onda com suceptibilidade elétrica de terceira ordem. Descrevemos a geração de pares de fotões em meios com elevado coeficiente de absorção, e identificamos regimes ótimos para o rácio contagens coincidentes/acidentais (CAR) e para a desigualdade de Clauser, Horne, Shimony, and Holt (CHSH), para o qual o compromisso entre perda do guia de onda e não-linearidades maximiza esses parâmetros.

Improving sampling, optimization and feature extraction in Boltzmann machines

L’apprentissage supervisé de réseaux hiérarchiques à grande échelle connaît présentement un succès fulgurant. Malgré cette effervescence, l’apprentissage non-supervisé représente toujours, selon plusieurs chercheurs, un élément clé de l’Intelligence Artificielle, où les agents doivent apprendre à partir d’un nombre potentiellement limité de données. Cette thèse s’inscrit dans cette pensée et aborde divers sujets de recherche liés au problème d’estimation de densité par l’entremise des machines de Boltzmann (BM), modèles graphiques probabilistes au coeur de l’apprentissage profond. Nos contributions touchent les domaines de l’échantillonnage, l’estimation de fonctions de partition, l’optimisation ainsi que l’apprentissage de représentations invariantes. Cette thèse débute par l’exposition d’un nouvel algorithme d'échantillonnage adaptatif, qui ajuste (de fa ̧con automatique) la température des chaînes de Markov sous simulation, afin de maintenir une vitesse de convergence élevée tout au long de l’apprentissage. Lorsqu’utilisé dans le contexte de l’apprentissage par maximum de vraisemblance stochastique (SML), notre algorithme engendre une robustesse accrue face à la sélection du taux d’apprentissage, ainsi qu’une meilleure vitesse de convergence. Nos résultats sont présent ́es dans le domaine des BMs, mais la méthode est générale et applicable à l’apprentissage de tout modèle probabiliste exploitant l’échantillonnage par chaînes de Markov. Tandis que le gradient du maximum de vraisemblance peut-être approximé par échantillonnage, l’évaluation de la log-vraisemblance nécessite un estimé de la fonction de partition. Contrairement aux approches traditionnelles qui considèrent un modèle donné comme une boîte noire, nous proposons plutôt d’exploiter la dynamique de l’apprentissage en estimant les changements successifs de log-partition encourus à chaque mise à jour des paramètres. Le problème d’estimation est reformulé comme un problème d’inférence similaire au filtre de Kalman, mais sur un graphe bi-dimensionnel, où les dimensions correspondent aux axes du temps et au paramètre de température. Sur le thème de l’optimisation, nous présentons également un algorithme permettant d’appliquer, de manière efficace, le gradient naturel à des machines de Boltzmann comportant des milliers d’unités. Jusqu’à présent, son adoption était limitée par son haut coût computationel ainsi que sa demande en mémoire. Notre algorithme, Metric-Free Natural Gradient (MFNG), permet d’éviter le calcul explicite de la matrice d’information de Fisher (et son inverse) en exploitant un solveur linéaire combiné à un produit matrice-vecteur efficace. L’algorithme est prometteur: en terme du nombre d’évaluations de fonctions, MFNG converge plus rapidement que SML. Son implémentation demeure malheureusement inefficace en temps de calcul. Ces travaux explorent également les mécanismes sous-jacents à l’apprentissage de représentations invariantes. À cette fin, nous utilisons la famille de machines de Boltzmann restreintes “spike & slab” (ssRBM), que nous modifions afin de pouvoir modéliser des distributions binaires et parcimonieuses. Les variables latentes binaires de la ssRBM peuvent être rendues invariantes à un sous-espace vectoriel, en associant à chacune d’elles, un vecteur de variables latentes continues (dénommées “slabs”). Ceci se traduit par une invariance accrue au niveau de la représentation et un meilleur taux de classification lorsque peu de données étiquetées sont disponibles. Nous terminons cette thèse sur un sujet ambitieux: l’apprentissage de représentations pouvant séparer les facteurs de variations présents dans le signal d’entrée. Nous proposons une solution à base de ssRBM bilinéaire (avec deux groupes de facteurs latents) et formulons le problème comme l’un de “pooling” dans des sous-espaces vectoriels complémentaires.

Essays in macro finance and monetary economics

Les questions abordées dans les deux premiers articles de ma thèse cherchent à comprendre les facteurs économiques qui affectent la structure à terme des taux d'intérêt et la prime de risque. Je construis des modèles non linéaires d'équilibre général en y intégrant des obligations de différentes échéances. Spécifiquement, le premier article a pour objectif de comprendre la relation entre les facteurs macroéconomiques et le niveau de prime de risque dans un cadre Néo-keynésien d'équilibre général avec incertitude. L'incertitude dans le modèle provient de trois sources : les chocs de productivité, les chocs monétaires et les chocs de préférences. Le modèle comporte deux types de rigidités réelles à savoir la formation des habitudes dans les préférences et les coûts d'ajustement du stock de capital. Le modèle est résolu par la méthode des perturbations à l'ordre deux et calibré à l'économie américaine. Puisque la prime de risque est par nature une compensation pour le risque, l'approximation d'ordre deux implique que la prime de risque est une combinaison linéaire des volatilités des trois chocs. Les résultats montrent qu'avec les paramètres calibrés, les chocs réels (productivité et préférences) jouent un rôle plus important dans la détermination du niveau de la prime de risque relativement aux chocs monétaires. Je montre que contrairement aux travaux précédents (dans lesquels le capital de production est fixe), l'effet du paramètre de la formation des habitudes sur la prime de risque dépend du degré des coûts d'ajustement du capital. Lorsque les coûts d'ajustement du capital sont élevés au point que le stock de capital est fixe à l'équilibre, une augmentation du paramètre de formation des habitudes entraine une augmentation de la prime de risque. Par contre, lorsque les agents peuvent librement ajuster le stock de capital sans coûts, l'effet du paramètre de la formation des habitudes sur la prime de risque est négligeable. Ce résultat s'explique par le fait que lorsque le stock de capital peut être ajusté sans coûts, cela ouvre un canal additionnel de lissage de consommation pour les agents. Par conséquent, l'effet de la formation des habitudes sur la prime de risque est amoindri. En outre, les résultats montrent que la façon dont la banque centrale conduit sa politique monétaire a un effet sur la prime de risque. Plus la banque centrale est agressive vis-à-vis de l'inflation, plus la prime de risque diminue et vice versa. Cela est due au fait que lorsque la banque centrale combat l'inflation cela entraine une baisse de la variance de l'inflation. Par suite, la prime de risque due au risque d'inflation diminue. Dans le deuxième article, je fais une extension du premier article en utilisant des préférences récursives de type Epstein -- Zin et en permettant aux volatilités conditionnelles des chocs de varier avec le temps. L'emploi de ce cadre est motivé par deux raisons. D'abord des études récentes (Doh, 2010, Rudebusch and Swanson, 2012) ont montré que ces préférences sont appropriées pour l'analyse du prix des actifs dans les modèles d'équilibre général. Ensuite, l'hétéroscedasticité est une caractéristique courante des données économiques et financières. Cela implique que contrairement au premier article, l'incertitude varie dans le temps. Le cadre dans cet article est donc plus général et plus réaliste que celui du premier article. L'objectif principal de cet article est d'examiner l'impact des chocs de volatilités conditionnelles sur le niveau et la dynamique des taux d'intérêt et de la prime de risque. Puisque la prime de risque est constante a l'approximation d'ordre deux, le modèle est résolu par la méthode des perturbations avec une approximation d'ordre trois. Ainsi on obtient une prime de risque qui varie dans le temps. L'avantage d'introduire des chocs de volatilités conditionnelles est que cela induit des variables d'état supplémentaires qui apportent une contribution additionnelle à la dynamique de la prime de risque. Je montre que l'approximation d'ordre trois implique que les primes de risque ont une représentation de type ARCH-M (Autoregressive Conditional Heteroscedasticty in Mean) comme celui introduit par Engle, Lilien et Robins (1987). La différence est que dans ce modèle les paramètres sont structurels et les volatilités sont des volatilités conditionnelles de chocs économiques et non celles des variables elles-mêmes. J'estime les paramètres du modèle par la méthode des moments simulés (SMM) en utilisant des données de l'économie américaine. Les résultats de l'estimation montrent qu'il y a une évidence de volatilité stochastique dans les trois chocs. De plus, la contribution des volatilités conditionnelles des chocs au niveau et à la dynamique de la prime de risque est significative. En particulier, les effets des volatilités conditionnelles des chocs de productivité et de préférences sont significatifs. La volatilité conditionnelle du choc de productivité contribue positivement aux moyennes et aux écart-types des primes de risque. Ces contributions varient avec la maturité des bonds. La volatilité conditionnelle du choc de préférences quant à elle contribue négativement aux moyennes et positivement aux variances des primes de risque. Quant au choc de volatilité de la politique monétaire, son impact sur les primes de risque est négligeable. Le troisième article (coécrit avec Eric Schaling, Alain Kabundi, révisé et resoumis au journal of Economic Modelling) traite de l'hétérogénéité dans la formation des attentes d'inflation de divers groupes économiques et de leur impact sur la politique monétaire en Afrique du sud. La question principale est d'examiner si différents groupes d'agents économiques forment leurs attentes d'inflation de la même façon et s'ils perçoivent de la même façon la politique monétaire de la banque centrale (South African Reserve Bank). Ainsi on spécifie un modèle de prédiction d'inflation qui nous permet de tester l'arrimage des attentes d'inflation à la bande d'inflation cible (3% - 6%) de la banque centrale. Les données utilisées sont des données d'enquête réalisée par la banque centrale auprès de trois groupes d'agents : les analystes financiers, les firmes et les syndicats. On exploite donc la structure de panel des données pour tester l'hétérogénéité dans les attentes d'inflation et déduire leur perception de la politique monétaire. Les résultats montrent qu'il y a évidence d'hétérogénéité dans la manière dont les différents groupes forment leurs attentes. Les attentes des analystes financiers sont arrimées à la bande d'inflation cible alors que celles des firmes et des syndicats ne sont pas arrimées. En effet, les firmes et les syndicats accordent un poids significatif à l'inflation retardée d'une période et leurs prédictions varient avec l'inflation réalisée (retardée). Ce qui dénote un manque de crédibilité parfaite de la banque centrale au vu de ces agents.

Effect of annealing on the spectral and nonlinear optical characteristics of thin films of nano-ZnO

The annealing effect on the spectral and nonlinear optical NLO characteristics of ZnO thin films deposited on quartz substrates by sol-gel process is investigated. As the annealing temperature increases from 300–1050 °C, there is a decrease in the band gap, which indicates the changes of the interface of ZnO. ZnO is reported to show two emission bands, an ultraviolet UV emission band and another in the green region. The intensity of the UV peak remains the same while the intensity of the visible peak increases with increase in annealing temperature. The role of oxygen in ZnO thin films during the annealing process is important to the change in optical properties. The mechanism of the luminescence suggests that UV luminescence of ZnO thin films is related to the transition from conduction band edge to valence band, and green luminescence is caused by the transition from deep donor level to valence band due to oxygen vacancies. The NLO response of these samples is studied using nanosecond laser pulses at off-resonance wavelengths. The nonlinear absorption coefficient increases from 2.9 ×10−6 to 1.0 ×10−4 m/W when the annealing temperature is increased from 300 to 1050 °C, mainly due to the enhancement of interfacial state and exciton oscillator strength. The third order optical susceptibility x(3) increases with increase in annealing temperature (T) within the range of our investigations. In the weak confinement regime, T2.4 dependence of x(3) is obtained for ZnO thin films. The role of annealing temperature on the optical limiting response is also studied.

Nonlinear optical characteristics of self-assembled films of ZnO

In the present work, we have investigated the nonlinear optical properties of self-assembled films formed from ZnO colloidal spheres by z-scan technique. The sign of the nonlinear component of refractive index of the material remains the same; however, a switching from reverse saturable absorption to saturable absorption has been observed as the material changes from colloid to self-assembled film. These different nonlinear characteristics can be mainly attributed to ZnO defect states and electronic effects when the colloidal solution is transformed into self-assembled monolayers. We investigated the intensity, wavelength and size dependence of saturable and reverse saturable absorption of ZnO self-assembled films and colloids. Values of the imaginary part of third-order susceptibility are calculated for particles of size in the range 20–300 nm at different intensity levels ranging from 40 to 325MW/cm2 within the wavelength range of 450–650 nm.

Modelling, control and supervision for a class of hybrid systems

The aim of this thesis is to narrow the gap between two different control techniques: the continuous control and the discrete event control techniques DES. This gap can be reduced by the study of Hybrid systems, and by interpreting as Hybrid systems the majority of large-scale systems. In particular, when looking deeply into a process, it is often possible to identify interaction between discrete and continuous signals. Hybrid systems are systems that have both continuous, and discrete signals. Continuous signals are generally supposed continuous and differentiable in time, since discrete signals are neither continuous nor differentiable in time due to their abrupt changes in time. Continuous signals often represent the measure of natural physical magnitudes such as temperature, pressure etc. The discrete signals are normally artificial signals, operated by human artefacts as current, voltage, light etc. Typical processes modelled as Hybrid systems are production systems, chemical process, or continuos production when time and continuous measures interacts with the transport, and stock inventory system. Complex systems as manufacturing lines are hybrid in a global sense. They can be decomposed into several subsystems, and their links. Another motivation for the study of Hybrid systems is the tools developed by other research domains. These tools benefit from the use of temporal logic for the analysis of several properties of Hybrid systems model, and use it to design systems and controllers, which satisfies physical or imposed restrictions. This thesis is focused in particular types of systems with discrete and continuous signals in interaction. That can be modelled hard non-linealities, such as hysteresis, jumps in the state, limit cycles, etc. and their possible non-deterministic future behaviour expressed by an interpretable model description. The Hybrid systems treated in this work are systems with several discrete states, always less than thirty states (it can arrive to NP hard problem), and continuous dynamics evolving with expression: with Ki ¡ Rn constant vectors or matrices for X components vector. In several states the continuous evolution can be several of them Ki = 0. In this formulation, the mathematics can express Time invariant linear system. By the use of this expression for a local part, the combination of several local linear models is possible to represent non-linear systems. And with the interaction with discrete events of the system the model can compose non-linear Hybrid systems. Especially multistage processes with high continuous dynamics are well represented by the proposed methodology. Sate vectors with more than two components, as third order models or higher is well approximated by the proposed approximation. Flexible belt transmission, chemical reactions with initial start-up and mobile robots with important friction are several physical systems, which profits from the benefits of proposed methodology (accuracy). The motivation of this thesis is to obtain a solution that can control and drive the Hybrid systems from the origin or starting point to the goal. How to obtain this solution, and which is the best solution in terms of one cost function subject to the physical restrictions and control actions is analysed. Hybrid systems that have several possible states, different ways to drive the system to the goal and different continuous control signals are problems that motivate this research. The requirements of the system on which we work is: a model that can represent the behaviour of the non-linear systems, and that possibilities the prediction of possible future behaviour for the model, in order to apply an supervisor which decides the optimal and secure action to drive the system toward the goal. Specific problems can be determined by the use of this kind of hybrid models are: - The unity of order. - Control the system along a reachable path. - Control the system in a safe path. - Optimise the cost function. - Modularity of control The proposed model solves the specified problems in the switching models problem, the initial condition calculus and the unity of the order models. Continuous and discrete phenomena are represented in Linear hybrid models, defined with defined eighth-tuple parameters to model different types of hybrid phenomena. Applying a transformation over the state vector : for LTI system we obtain from a two-dimensional SS a single parameter, alpha, which still maintains the dynamical information. Combining this parameter with the system output, a complete description of the system is obtained in a form of a graph in polar representation. Using Tagaki-Sugeno type III is a fuzzy model which include linear time invariant LTI models for each local model, the fuzzyfication of different LTI local model gives as a result a non-linear time invariant model. In our case the output and the alpha measure govern the membership function. Hybrid systems control is a huge task, the processes need to be guided from the Starting point to the desired End point, passing a through of different specific states and points in the trajectory. The system can be structured in different levels of abstraction and the control in three layers for the Hybrid systems from planning the process to produce the actions, these are the planning, the process and control layer. In this case the algorithms will be applied to robotics ¡V a domain where improvements are well accepted ¡V it is expected to find a simple repetitive processes for which the extra effort in complexity can be compensated by some cost reductions. It may be also interesting to implement some control optimisation to processes such as fuel injection, DC-DC converters etc. In order to apply the RW theory of discrete event systems on a Hybrid system, we must abstract the continuous signals and to project the events generated for these signals, to obtain new sets of observable and controllable events. Ramadge & Wonham¡¦s theory along with the TCT software give a Controllable Sublanguage of the legal language generated for a Discrete Event System (DES). Continuous abstraction transforms predicates over continuous variables into controllable or uncontrollable events, and modifies the set of uncontrollable, controllable observable and unobservable events. Continuous signals produce into the system virtual events, when this crosses the bound limits. If this event is deterministic, they can be projected. It is necessary to determine the controllability of this event, in order to assign this to the corresponding set, , controllable, uncontrollable, observable and unobservable set of events. Find optimal trajectories in order to minimise some cost function is the goal of the modelling procedure. Mathematical model for the system allows the user to apply mathematical techniques over this expression. These possibilities are, to minimise a specific cost function, to obtain optimal controllers and to approximate a specific trajectory. The combination of the Dynamic Programming with Bellman Principle of optimality, give us the procedure to solve the minimum time trajectory for Hybrid systems. The problem is greater when there exists interaction between adjacent states. In Hybrid systems the problem is to determine the partial set points to be applied at the local models. Optimal controller can be implemented in each local model in order to assure the minimisation of the local costs. The solution of this problem needs to give us the trajectory to follow the system. Trajectory marked by a set of set points to force the system to passing over them. Several ways are possible to drive the system from the Starting point Xi to the End point Xf. Different ways are interesting in: dynamic sense, minimum states, approximation at set points, etc. These ways need to be safe and viable and RchW. And only one of them must to be applied, normally the best, which minimises the proposed cost function. A Reachable Way, this means the controllable way and safe, will be evaluated in order to obtain which one minimises the cost function. Contribution of this work is a complete framework to work with the majority Hybrid systems, the procedures to model, control and supervise are defined and explained and its use is demonstrated. Also explained is the procedure to model the systems to be analysed for automatic verification. Great improvements were obtained by using this methodology in comparison to using other piecewise linear approximations. It is demonstrated in particular cases this methodology can provide best approximation. The most important contribution of this work, is the Alpha approximation for non-linear systems with high dynamics While this kind of process is not typical, but in this case the Alpha approximation is the best linear approximation to use, and give a compact representation.

A high-order arbitrarily unstructured finite-volume model of the global atmosphere: tests solving the shallow-water equations

Simulations of the global atmosphere for weather and climate forecasting require fast and accurate solutions and so operational models use high-order finite differences on regular structured grids. This precludes the use of local refinement; techniques allowing local refinement are either expensive (eg. high-order finite element techniques) or have reduced accuracy at changes in resolution (eg. unstructured finite-volume with linear differencing). We present solutions of the shallow-water equations for westerly flow over a mid-latitude mountain from a finite-volume model written using OpenFOAM. A second/third-order accurate differencing scheme is applied on arbitrarily unstructured meshes made up of various shapes and refinement patterns. The results are as accurate as equivalent resolution spectral methods. Using lower order differencing reduces accuracy at a refinement pattern which allows errors from refinement of the mountain to accumulate and reduces the global accuracy over a 15 day simulation. We have therefore introduced a scheme which fits a 2D cubic polynomial approximately on a stencil around each cell. Using this scheme means that refinement of the mountain improves the accuracy after a 15 day simulation. This is a more severe test of local mesh refinement for global simulations than has been presented but a realistic test if these techniques are to be used operationally. These efficient, high-order schemes may make it possible for local mesh refinement to be used by weather and climate forecast models.

Simultaneous analysis of v1, v4, 2v2, v2+v5, and 2v5 bands of 12CH3F

The Fourier-transform spectrum of CH3F from 2800 to 3100 cm−1, obtained by Guelachvili in Orsay at a resolution of about 0.003 cm−1, was analyzed. The effective Hamiltonian used contained all symmetry allowed interactions up to second order in the Amat-Nielsen classification, together with selected third-order terms, amongst the set of nine vibrational basis functions represented by the states ν1(A1), ν4(E), 2ν2(A1), ν2 + ν5(E), 2ν50(A1), and 2ν5±2(E). A number of strong Fermi and Coriolis resonances are involved. The vibrational Hamiltonian matrix was not factorized beyond the requirements of symmetry. A total of 59 molecular parameters were refined in a simultaneous least-squares analysis to over 1500 upper-state energy levels for J ≤ 20 with a standard deviation of 0.013 cm−1. Although the standard deviation remains an order of magnitude greater than the precision of the measurements, this work breaks new ground in the simultaneous analysis of interacting symmetric top vibrational levels, in terms of the number of interacting vibrational states and the number of parameters in the Hamiltonian.

Pseudolikelihood equations for Potts MRF model parameter estimation on higher order neighborhood systems

This letter presents pseudolikelihood equations for the estimation of the Potts Markov random field model parameter on higher order neighborhood systems. The derived equation for second-order systems is a significantly reduced version of a recent result found in the literature (from 67 to 22 terms). Also, with the proposed method, a completely original equation for Potts model parameter estimation in third-order systems was obtained. These equations allow the modeling of less restrictive contextual systems for a large number of applications in a computationally feasible way. Experiments with both simulated and real remote sensing images provided good results.

ENO adaptive method for solving one-dimensional conservation laws

In this work an efficient third order non-linear finite difference scheme for solving adaptively hyperbolic systems of one-dimensional conservation laws is developed. The method is based oil applying to the solution of the differential equation an interpolating wavelet transform at each time step, generating a multilevel representation for the solution, which is thresholded and a sparse point representation is generated. The numerical fluxes obtained by a Lax-Friedrichs flux splitting are evaluated oil the sparse grid by an essentially non-oscillatory (ENO) approximation, which chooses the locally smoothest stencil among all the possibilities for each point of the sparse grid. The time evolution of the differential operator is done on this sparse representation by a total variation diminishing (TVD) Runge-Kutta method. Four classical examples of initial value problems for the Euler equations of gas dynamics are accurately solved and their sparse solutions are analyzed with respect to the threshold parameters, confirming the efficiency of the wavelet transform as an adaptive grid generation technique. (C) 2008 IMACS. Published by Elsevier B.V. All rights reserved.

Morfometria de microbacias do Córrego Rico, afluente do Rio Mogi-Guaçu, Estado de São Paulo, Brasil

Este trabalho teve como objetivo avaliar as características morfométricas das microbacias (2ª, 3ª, 4ª e 5ª ordens de magnitude) da bacia hidrográfica do córrego Rico, sub-bacia do Rio Mogi-Guaçu, localizada na região administrativa de Ribeirão Preto, Estado de São Paulo, Brasil. Para tanto, foram determinados os parâmetros físicos e a configuração topográfica natural do sistema de drenagem. Os procedimentos para a obtenção dos dados foram fundamentados em técnicas de sensoriamento remoto e geoprocessamento. A partir da vetorização das cartas topográficas correspondentes à área de estudo, realizou-se a análise morfométrica quanto às características dimensionais, do padrão de drenagem e do relevo no sistema de informação geográfica ArcView. A microbacia é considerada de sexta ordem de magnitude, com área estimada de 542 km², com 85 microbacias de segunda ordem, 22 de terceira, sete de quarta ordem e duas de quinta. Utilizando o critério geométrico, na disposição fluvial das sub-bacias de cabeceiras observou-se a predominância dos modelos dendríticos e subdendríticos, enquanto a jusante predominava o modelo subparalelo, respectivamente, nas áreas de ocorrências dos arenitos Bauru e rochas efusivas básicas.