Equalização neural aplicada a sistemas com modulação bidimensional em fibra óptica

Nowadays, optic fiber is one of the most used communication methods, mainly due to the fact that the data transmission rates of those systems exceed all of the other means of digital communication. Despite the great advantage, there are problems that prevent full utilization of the optical channel: by increasing the transmission speed and the distances involved, the data is subjected to non-linear inter symbolic interference caused by the dispersion phenomena in the fiber. Adaptive equalizers can be used to solve this problem, they compensate non-ideal responses of the channel in order to restore the signal that was transmitted. This work proposes an equalizer based on artificial neural networks and evaluates its performance in optical communication systems. The proposal is validated through a simulated optic channel and the comparison with other adaptive equalization techniques

Determinação de dados de equilíbrio de fases para sistemas aquosos com eletrólitos

In the present work are established initially the fundamental relationships of thermodynamics that govern the equilibrium between phases, the models used for the description of the behavior non ideal of the liquid and vapor phases in conditions of low pressures. This work seeks the determination of vapor-liquid equilibrium (VLE) data for a series of multicomponents mixtures of saturated aliphatic hydrocarbons, prepared synthetically starting from substances with analytical degree and the development of a new dynamic cell with circulation of the vapor phase. The apparatus and experimental procedures developed are described and applied for the determination of VLE data. VLE isobarics data were obtained through a Fischer s ebulliometer of circulation of both phases, for the systems pentane + dodecane, heptane + dodecane and decane + dodecane. Using the two new dynamic cells especially projected, of easy operation and low cost, with circulation of the vapor phase, data for the systems heptane + decane + dodecane, acetone + water, tween 20 + dodecane, phenol + water and distillation curves of a gasoline without addictive were measured. Compositions of the equilibrium phases were found by densimetry, chromatography, and total organic carbon analyzer. Calibration curves of density versus composition were prepared from synthetic mixtures and the behavior excess volumes were evaluated. The VLE data obtained experimentally for the hydrocarbon and aqueous systems were submitted to the test of thermodynamic consistency, as well as the obtained from the literature data for another binary systems, mainly in the bank DDB (Dortmund Data Bank), where the Gibbs-Duhem equation is used obtaining a satisfactory data base. The results of the thermodynamic consistency tests for the binary and ternary systems were evaluated in terms of deviations for applications such as model development. Later, those groups of data (tested and approved) were used in the KijPoly program for the determination of the binary kij parameters of the cubic equations of state original Peng-Robinson and with the expanded alpha function. These obtained parameters can be applied for simulation of the reservoirs petroleum conditions and of the several distillation processes found in the petrochemistry industry, through simulators. The two designed dynamic cells used equipments of national technology for the determination of VLE data were well succeed, demonstrating efficiency and low cost. Multicomponents systems, mixtures of components of different molecular weights and also diluted solutions may be studied in these developed VLE cells

Determinação de Dados de Equilíbrio Líquido-Vapor para Sistemas Hidrocarbonetos e Desenvolvimento de uma Nova Célula Dinâmica

In the present work are established initially the fundamental relationships of thermodynamics that govern the equilibrium between phases, the models used for the description of the behavior non ideal of the liquid and vapor phases in conditions of low pressures. This work seeks the determination of vapor-liquid equilibrium (VLE) data for a series of multicomponents mixtures of saturated aliphatic hydrocarbons, prepared synthetically starting from substances with analytical degree and the development of a new dynamic cell with circulation of the vapor phase. The apparatus and experimental procedures developed are described and applied for the determination of VLE data. VLE isobarics data were obtained through a Fischer's ebulliometer of circulation of both phases, for the systems pentane + dodecane, heptane + dodecane and decane + dodecane. Using the two new dynamic cells especially projected, of easy operation and low cost, with circulation of the vapor phase, data for the systems heptane + decane + dodecane, acetone + water, tween 20 + dodecane, phenol + water and distillation curves of a gasoline without addictive were measured. Compositions of the equilibrium phases were found by densimetry, chromatography, and total organic carbon analyzer. Calibration curves of density versus composition were prepared from synthetic mixtures and the behavior excess volumes were evaluated. The VLE data obtained experimentally for the hydrocarbon and aqueous systems were submitted to the test of thermodynamic consistency, as well as the obtained from the literature data for another binary systems, mainly in the bank DDB (Dortmund Data Bank), where the Gibbs-Duhem equation is used obtaining a satisfactory data base. The results of the thermodynamic consistency tests for the binary and ternary systems were evaluated in terms of deviations for applications such as model development. Later, those groups of data (tested and approved) were used in the KijPoly program for the determination of the binary kij parameters of the cubic equations of state original Peng-Robinson and with the expanded alpha function. These obtained parameters can be applied for simulation of the reservoirs petroleum conditions and of the several distillation processes found in the petrochemistry industry, through simulators. The two designed dynamic cells used equipments of national technology for the determination Humberto Neves Maia de Oliveira Tese de Doutorado PPGEQ/PRH-ANP 14/UFRN of VLE data were well succeed, demonstrating efficiency and low cost. Multicomponents systems, mixtures of components of different molecular weights and also diluted solutions may be studied in these developed VLE cells

Critério de correntropia no treinamento de redes fuzzy wavelet neural networks para identificação de sistemas dinâmicos não lineares

The great interest in nonlinear system identification is mainly due to the fact that a large amount of real systems are complex and need to have their nonlinearities considered so that their models can be successfully used in applications of control, prediction, inference, among others. This work evaluates the application of Fuzzy Wavelet Neural Networks (FWNN) to identify nonlinear dynamical systems subjected to noise and outliers. Generally, these elements cause negative effects on the identification procedure, resulting in erroneous interpretations regarding the dynamical behavior of the system. The FWNN combines in a single structure the ability to deal with uncertainties of fuzzy logic, the multiresolution characteristics of wavelet theory and learning and generalization abilities of the artificial neural networks. Usually, the learning procedure of these neural networks is realized by a gradient based method, which uses the mean squared error as its cost function. This work proposes the replacement of this traditional function by an Information Theoretic Learning similarity measure, called correntropy. With the use of this similarity measure, higher order statistics can be considered during the FWNN training process. For this reason, this measure is more suitable for non-Gaussian error distributions and makes the training less sensitive to the presence of outliers. In order to evaluate this replacement, FWNN models are obtained in two identification case studies: a real nonlinear system, consisting of a multisection tank, and a simulated system based on a model of the human knee joint. The results demonstrate that the application of correntropy as the error backpropagation algorithm cost function makes the identification procedure using FWNN models more robust to outliers. However, this is only achieved if the gaussian kernel width of correntropy is properly adjusted.

Memorial de formação: um dispositivo de pesquisa ação - formação

La recherche prend comme point de départ la dimension formative du mémoire de formation, considerée comme constitutive de l´écriture de soi, et cherche à problématiser cette dimension au tour du questionnement suivant: Comment le mémoire de formation devient-il un instrument de recherche-action-formation? Les analyses s´appuient sur les principes théoriques du paradigme anthropoformateur, proposé par Pineau (2005), les études réalisées par Passeggi (2006ª, 2006b, 2007, 2008ª, 2008b) sur les mémoires, les travaux de recherche de Nóvoa (1988, 1995), de Josso (2004), de Souza (2006) et de Fontana (2000), qui conçoivent la formação du point de vue de l´ apprenant. L´univers de la recherche s´est circonscrit à la situation de formation des éducateurs de la zone rurale, étudiants en Pédagogie dans le PROFORMAÇÃO (CAMEAM), à l´Univeristé de l´Etat du Rio Grande du Nord (UERN), pendant le second semestre de 2005. La recherche a croisé diférents types de démarche pour recueillir les données empiriques: l´observation du processus d´élaboration des mémoires; un questionnaire; des entretiens informels avec les enseignants en formation et avec les formateurs; et 09 mémoires, écrits par les participants de la recherche. Les analyses des données empiriques montrent que l´écriture des mémoires, en tant que démarche de recherche-action-formation, révelent que la dimension formative se dédouble en d´autres dimensions: etnosociologique, heuristique, herméneutique, social et afective, autopoiétique et politique. Dans la quête de soi (recherche), mise en oeuvre dans et par l´écriture (action), chaque narrateur construit de nouveaux sens à la vie et (re)signifient les représentations de soi (formation). Les résultats confirment la richesse et les potentialités du mémoire, même dans des conditions non ideal, ce qui permet d´affirmer as valeur travail académique important dans la formation des enseignants

Identificação não linear usando uma rede fuzzy wavelet neural network modificada

In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed

Processo de difusão com agregação e reorganização espontânea em uma rede 2D

Difusive processes are extremely common in Nature. Many complex systems, such as microbial colonies, colloidal aggregates, difusion of fluids, and migration of populations, involve a large number of similar units that form fractal structures. A new model of difusive agregation was proposed recently by Filoche and Sapoval [68]. Based on their work, we develop a model called Difusion with Aggregation and Spontaneous Reorganization . This model consists of a set of particles with excluded volume interactions, which perform random walks on a square lattice. Initially, the lattice is occupied with a density p = N/L2 of particles occupying distinct, randomly chosen positions. One of the particles is selected at random as the active particle. This particle executes a random walk until it visits a site occupied by another particle, j. When this happens, the active particle is rejected back to its previous position (neighboring particle j), and a new active particle is selected at random from the set of N particles. Following an initial transient, the system attains a stationary regime. In this work we study the stationary regime, focusing on scaling properties of the particle distribution, as characterized by the pair correlation function ø(r). The latter is calculated by averaging over a long sequence of configurations generated in the stationary regime, using systems of size 50, 75, 100, 150, . . . , 700. The pair correlation function exhibits distinct behaviors in three diferent density ranges, which we term subcritical, critical, and supercritical. We show that in the subcritical regime, the particle distribution is characterized by a fractal dimension. We also analyze the decay of temporal correlations