A time-domain probe method for three-dimensional rough surface reconstructions

The task of this paper is to develop a Time-Domain Probe Method for the reconstruction of impenetrable scatterers. The basic idea of the method is to use pulses in the time domain and the time-dependent response of the scatterer to reconstruct its location and shape. The method is based on the basic causality principle of timedependent scattering. The method is independent of the boundary condition and is applicable for limited aperture scattering data. In particular, we discuss the reconstruction of the shape of a rough surface in three dimensions from time-domain measurements of the scattered field. In practise, measurement data is collected where the incident field is given by a pulse. We formulate the time-domain fieeld reconstruction problem equivalently via frequency-domain integral equations or via a retarded boundary integral equation based on results of Bamberger, Ha-Duong, Lubich. In contrast to pure frequency domain methods here we use a time-domain characterization of the unknown shape for its reconstruction. Our paper will describe the Time-Domain Probe Method and relate it to previous frequency-domain approaches on sampling and probe methods by Colton, Kirsch, Ikehata, Potthast, Luke, Sylvester et al. The approach significantly extends recent work of Chandler-Wilde and Lines (2005) and Luke and Potthast (2006) on the timedomain point source method. We provide a complete convergence analysis for the method for the rough surface scattering case and provide numerical simulations and examples.

Trefftz discontinuous Galerkin methods for acoustic scattering on locally refined meshes

We extend the a priori error analysis of Trefftz-discontinuous Galerkin methods for time-harmonic wave propagation problems developed in previous papers to acoustic scattering problems and locally refined meshes. To this aim, we prove refined regularity and stability results with explicit dependence of the stability constant on the wave number for non convex domains with non connected boundaries. Moreover, we devise a new choice of numerical flux parameters for which we can prove L2-error estimates in the case of locally refined meshes near the scatterer. This is the setting needed to develop a complete hp-convergence analysis.

Comments on "A blind signal separation method for multiuser communications"

This correspondence first shows that the global convergence analysis of the method proposed in the above paper is incomplete. Then we provide a counter example to show that the sufficient condition for global convergence is incorrect.

Pseudoconvex proximal splitting for L∞problems in multiview geometry

In this paper we study optimization methods for minimizing large-scale pseudoconvex L∞problems in multiview geometry. We present a novel algorithm for solving this class of problem based on proximal splitting methods. We provide a brief derivation of the proposed method along with a general convergence analysis. The resulting meta-algorithm requires very little effort in terms of implementation and instead makes use of existing advanced solvers for non-linear optimization. Preliminary experiments on a number of real image datasets indicate that the proposed method experimentally matches or outperforms current state-of-the-art solvers for this class of problems.

Caracterização de estruturas planares com substratos Iso/Anisotrópicos truncados através da técnica da ressonância transversa modificada

This work presents a theoretical and numerical analysis using the transverse resonance technique (TRT) and a proposed MTRT applied in the analysis of the dispersive characteristics of microstrip lines built on truncated isotropic and anisotropic dielectric substrates. The TRT uses the transmission lines model in the transversal section of the structure, allowing to analyze its dispersive behavior. The difference between TRT and MTRT consists basically of the resonance direction. While in the TRT the resonance is calculated in the same direction of the metallic strip normal axis, the MTRT considers the resonance in the metallic strip parallel plane. Although the application of the MTRT results in a more complex equivalent circuit, its use allows some added characterization, like longitudinal section electric mode (LSE) and longitudinal section magnetic mode (LSM), microstrips with truncated substrate, or structures with different dielectric regions. A computer program using TRT and MTRT proposed in this work is implemented for the characterization of microstrips on truncated isotropic and anisotropic substrates. In this analysis, propagating and evanescent modes are considered. Thus, it is possible to characterize both the dominant and higher order modes of the structure. Numerical results are presented for the effective permittivity, characteristic impedance and relative phase velocity for microstrip lines with different parameters and dimensions of the dielectric substrate. Agreement with the results obtained in the literature are shown, as well as experimental results. In some cases, the convergence analysis is also performed by considering the limiting conditions, like particular cases of isotropic materials or structures with dielectric of infinite size found in the literature. The numerical convergence of the formulation is also analyzed. Finally, conclusions and suggestions for the continuity of this work are presented

Algoritmos genéticos: uso de lógica nebulosa e análise de convergência por cadeia de Markov

In this work, the Markov chain will be the tool used in the modeling and analysis of convergence of the genetic algorithm, both the standard version as for the other versions that allows the genetic algorithm. In addition, we intend to compare the performance of the standard version with the fuzzy version, believing that this version gives the genetic algorithm a great ability to find a global optimum, own the global optimization algorithms. The choice of this algorithm is due to the fact that it has become, over the past thirty yares, one of the more importan tool used to find a solution of de optimization problem. This choice is due to its effectiveness in finding a good quality solution to the problem, considering that the knowledge of a good quality solution becomes acceptable given that there may not be another algorithm able to get the optimal solution for many of these problems. However, this algorithm can be set, taking into account, that it is not only dependent on how the problem is represented as but also some of the operators are defined, to the standard version of this, when the parameters are kept fixed, to their versions with variables parameters. Therefore to achieve good performance with the aforementioned algorithm is necessary that it has an adequate criterion in the choice of its parameters, especially the rate of mutation and crossover rate or even the size of the population. It is important to remember that those implementations in which parameters are kept fixed throughout the execution, the modeling algorithm by Markov chain results in a homogeneous chain and when it allows the variation of parameters during the execution, the Markov chain that models becomes be non - homogeneous. Therefore, in an attempt to improve the algorithm performance, few studies have tried to make the setting of the parameters through strategies that capture the intrinsic characteristics of the problem. These characteristics are extracted from the present state of execution, in order to identify and preserve a pattern related to a solution of good quality and at the same time that standard discarding of low quality. Strategies for feature extraction can either use precise techniques as fuzzy techniques, in the latter case being made through a fuzzy controller. A Markov chain is used for modeling and convergence analysis of the algorithm, both in its standard version as for the other. In order to evaluate the performance of a non-homogeneous algorithm tests will be applied to compare the standard fuzzy algorithm with the genetic algorithm, and the rate of change adjusted by a fuzzy controller. To do so, pick up optimization problems whose number of solutions varies exponentially with the number of variables

Uma abordagem para problemas e controle ótimo via métodos de Runge-Kutta e análise de erro

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A vulnerabilidade no esporte e a exposição às novas mídias: um estudo sobre o twitter

Pós-graduação em Desenvolvimento Humano e Tecnologias - IBRC

Estudos teóricos e numéricos de escoamentos com escorregamento

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Influence of crown-to-implant ratio, retention system, restorative material, and occlusal loading on stress concentrations in single short implants

Purpose: The aim of this study was to assess the contributions of some prosthetic parameters such as crown-to-implant (C/I) ratio, retention system, restorative material, and occlusal loading on stress concentrations within a single posterior crown supported by a short implant. Materials and Methods: Computer-aided design software was used to create 32 finite element models of an atrophic posterior partially edentulous mandible with a single external-hexagon implant (5 mm wide × 7 mm long) in the first molar region. Finite element analysis software with a convergence analysis of 5% to mesh refinement was used to evaluate the effects of C/I ratio (1:1; 1.5:1; 2:1, or 2.5:1), prosthetic retention system (cemented or screwed), and restorative material (metal-ceramic or all ceramic). The crowns were loaded with simulated normal or traumatic occlusal forces. The maximum principal stress (σmax) for cortical and cancellous bone and von Mises stress (σvM) for the implant and abutment screw were computed and analyzed. The percent contribution of each variable to the stress concentration was calculated from the sum of squares analysis. Results: Traumatic occlusion and a high C/I ratio increased stress concentrations. The C/I ratio was responsible for 11.45% of the total stress in the cortical bone, whereas occlusal loading contributed 70.92% to the total stress in the implant. The retention system contributed 0.91% of the total stress in the cortical bone. The restorative material was responsible for only 0.09% of the total stress in the cancellous bone. Conclusion: Occlusal loading was the most important stress concentration factor in the finite element model of a single posterior crown supported by a short implant.

Problems in the classical calculus of variations

This dissertation concerns convergence analysis for nonparametric problems in the calculus of variations and sufficient conditions for weak local minimizer of a functional for both nonparametric and parametric problems. Newton's method in infinite-dimensional space is proved to be well-defined and converges quadratically to a weak local minimizer of a functional subject to certain boundary conditions. Sufficient conditions for global converges are proposed and a well-defined algorithm based on those conditions is presented and proved to converge. Finite element discretization is employed to achieve an implementable line-search-based quasi-Newton algorithm and a proof of convergence of the discretization of the algorithm is included. This work also proposes sufficient conditions for weak local minimizer without using the language of conjugate points. The form of new conditions is consistent with the ones in finite-dimensional case. It is believed that the new form of sufficient conditions will lead to simpler approaches to verify an extremal as local minimizer for well-known problems in calculus of variations.

Modelagem estocástica da dispersão axial: aplicação em um reator tubular de polimerização.

Reatores tubulares de polimerização podem apresentar um perfil de velocidade bastante distorcido. Partindo desta observação, um modelo estocástico baseado no modelo de dispersão axial foi proposto para a representação matemática da fluidodinâmica de um reator tubular para produção de poliestireno. A equação diferencial foi obtida inserindo a aleatoriedade no parâmetro de dispersão, resultando na adição de um termo estocástico ao modelo capaz de simular as oscilações observadas experimentalmente. A equação diferencial estocástica foi discretizada e resolvida pelo método Euler-Maruyama de forma satisfatória. Uma função estimadora foi desenvolvida para a obtenção do parâmetro do termo estocástico e o parâmetro do termo determinístico foi calculado pelo método dos mínimos quadrados. Uma análise de convergência foi conduzida para determinar o número de elementos da discretização e o modelo foi validado através da comparação de trajetórias e de intervalos de confiança computacionais com dados experimentais. O resultado obtido foi satisfatório, o que auxilia na compreensão do comportamento fluidodinâmico complexo do reator estudado.

A class of self-stabilizing MCA learning algorithms

In this letter, we propose a class of self-stabilizing learning algorithms for minor component analysis (MCA), which includes a few well-known MCA learning algorithms. Self-stabilizing means that the sign of the weight vector length change is independent of the presented input vector. For these algorithms, rigorous global convergence proof is given and the convergence rate is also discussed. By combining the positive properties of these algorithms, a new learning algorithm is proposed which can improve the performance. Simulations are employed to confirm our theoretical results.

Steffensen Methods for Solving Generalized Equations

2000 Mathematics Subject Classification: 65G99, 65K10, 47H04.

Algoritmo modificado de PSO matricial aplicado a identificação de sistemas com análise de convergência

Recentemente diversas técnicas de computação evolucionárias têm sido utilizadas em áreas como estimação de parâmetros de processos dinâmicos lineares e não lineares ou até sujeitos a incertezas. Isso motiva a utilização de algoritmos como o otimizador por nuvem de partículas (PSO) nas referidas áreas do conhecimento. Porém, pouco se sabe sobre a convergência desse algoritmo e, principalmente, as análises e estudos realizados têm se concentrado em resultados experimentais. Por isso, é objetivo deste trabalho propor uma nova estrutura para o PSO que permita analisar melhor a convergência do algoritmo de forma analítica. Para isso, o PSO é reestruturado para assumir uma forma matricial e reformulado como um sistema linear por partes. As partes serão analisadas de forma separada e será proposta a inserção de um fator de esquecimento que garante que a parte mais significativa deste sistema possua autovalores dentro do círculo de raio unitário. Também será realizada a análise da convergência do algoritmo como um todo, utilizando um critério de convergência quase certa, aplicável a sistemas chaveados. Na sequência, serão realizados testes experimentais de maneira a verificar o comportamento dos autovalores após a inserção do fator de esquecimento. Posteriormente, os algoritmos de identificação de parâmetros tradicionais serão combinados com o PSO matricial, de maneira a tornar os resultados da identificação tão bons ou melhores que a identificação apenas com o PSO ou, apenas com os algoritmos tradicionais. Os resultados mostram a convergência das partículas em uma região delimitada e que as funções obtidas após a combinação do algoritmo PSO matricial com os algoritmos convencionais, apresentam maior generalização para o sistema apresentado. As conclusões a que se chega é que a hibridização, apesar de limitar a busca por uma partícula mais apta do PSO, permite um desempenho mínimo para o algoritmo e ainda possibilita melhorar o resultado obtido com os algoritmos tradicionais, permitindo a representação do sistema aproximado em quantidades maiores de frequências.