Orientadores: Wagner Caradori do Amaral, Ricardo Jose Gabrielli Barreto Campello / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-14T00:00:28Z (GMT). No. of bitstreams: 1 Rosa_Alexda_D.pdf: 1534572 bytes, checksum: 9100bf7dc7bd642daebdac3e973c668c (MD5) Previous issue date: 2009 / Resumo: Este trabalho enfoca a modelagem de sistemas não-lineares usando modelos de Volterra com funções de base ortonormal (Orthonormal Basis Functions - OBF). Os modelos de Volterra representam uma generalização do modelo de resposta ao impulso para a descrição de sistemas não-lineares e, em geral, exigem um elevado número de termos para representar os kernels de Volterra. Esta desvantagem pode ser superada representando-se os kernels usando um conjunto de funções ortonormais. O modelo resultante, conhecido como modelo OBF-Volterra, pode ser truncado em um n'umero menor de termos se as funções da base forem projetadas adequadamente. O problema central é como selecionar os polos livres que completamente parametrizam estas funções, particularmente as funções de Kautz e as funções ortonormais generalizadas (Generalized Orthonormal Basis Functions - GOBF). Uma das abordagens adotadas para resolver este problema envolve a minimização de um limitante superior para o erro resultante do truncamento da expansao do kernel. Cada kernel multidimensional é decomposto em um conjunto de bases de Kautz independentes, em que cada base é parametrizada por um par individual de pólos complexos conjugados com a intenção de representar a dinamica dominante do kernel ao longo de uma dimensão particular. Obtem-se uma solução analítica para um dos parâmetros de Kautz, válida para modelos de Volterra de qualquer ordem. Outra abordagem envolve a otimização numerica das bases de funções ortonormais usadas para a aproximação de sistemas dinamicos. Esta estrategia e baseada no cálculo de expressões analíticas para os gradientes da sa?da dos filtros ortonormais com relação aos pólos da base. Estes gradientes fornecem direções de busca exatas para otimizar os pólos de uma dada base ortonormal. As direções de busca, por sua vez, podem ser usadas como parte de um procedimento de otimização para obter o mínimo de uma função de custo que leva em consideração o erro de estimação da saída do sistema. As expressões relativas à base de Kautz e à base GOBF são obtidas. A metodologia proposta conta somente com dados entrada-sa'?da medidos do sistema a ser modelado, isto é, não se exige nenhuma informação prévia sobre os kernels de Volterra. Exemplos de simulação ilustram a aplicação desta abordagem para a modelagem de sistemas lineares e não-lineares, incluindo um sistema real de levitação magnética com comportamento oscilatorio. Por ultimo, estuda-se a representação de sistemas dinâmicos incertos baseada em modelos com incerteza estruturada. A incerteza de um conjunto de kernels de Volterra e mapeada em intervalos de pertinência que definem os coeficientes da expansão ortonormal. Condições adicionais são propostas para garantir que todos os kernels do processo sejam representados pelo modelo, o que permite estimar os limites das incertezas / Abstract: This work is concerned with the modeling of nonlinear systems using Volterra models with orthonormal basis functions (OBF). Volterra models represent a generalization of the impulse response model for the description of nonlinear systems and, in general, require a large number of terms for representing the Volterra kernels. Such a drawback can be overcome by representing the kernels using a set of orthonormal functions. The resulting model, so-called OBF-Volterra model, can be truncated into fewer terms if the basis functions are properly designed. The underlying problem is how to select the free-design poles that fully parameterize these functions, particularly the two-parameter Kautz functions and the Generalized Orthonormal Basis Functions (GOBF). One of the approaches adopted to solve this problem involves minimizing an upper bound for the error resulting from the truncation of the kernel expansion. Each multidimensional kernel is decomposed into a set of independent Kautz bases, in which every basis is parameterized by an individual pair of complex conjugate poles intended to represent the dominant dynamic of the kernel along a particular dimension. An analytical solution for one of the Kautz parameters, valid for Volterra models of any order, is derived. Other approach involves the numerical optimization of orthonormal bases of functions used for approximation of dynamic systems. This strategy is based on the computation of analytical expressions for the gradients of the output of the orthonormal filters with respect to the basis poles. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into consideration the error of estimation of the system output. The expressions relative to the Kautz basis and to the GOBF are addressed. The proposed methodology relies solely on input-output data measured from the system to be modeled, i.e., no previous information about the Volterra kernels is required. Simulation examples illustrate the application of this approach to the modeling of linear and nonlinear systems, including a real magnetic levitation system with oscillatory behavior. At last, the representation of uncertain systems based on models having structured uncertainty is studied. The uncertainty of a set of Volterra kernels is mapped on to intervals defining the coefficients of the orthonormal expansion. Additional conditions are proposed to guarantee that all the process kernels to be represented by the model, which allows estimating the uncertainty bounds / Doutorado / Automação / Doutor em Engenharia Elétrica

Volterra Series (VS) is often used in the analysis of mildly nonlinear circuits. In this approach, nonlinear circuit analysis is converted into the analysis of a series of linear circuits. The main benefit of this approach is that linear circuit analysis is well established and direct frequency domain analysis of a nonlinear circuit becomes possible. Sensitivity analysis is useful in comparing the quality of two designs and the evaluation of gradient, Jacobian or Hessian matrices, in analog Computer Aided Design. This thesis presents, for the first time, the sensitivity analysis of mildly nonlinear circuits in the frequency domain as an extension of the VS approach. To overcome efficiency limitation due to multiple mixing effects, Nonlinear Transfer Matrix (NTM) is introduced. It is the first explicit analytical representation of the complicated multiple mixing effects. The application of NTM in sensitivity analysis is capable of two orders of magnitude speedup. Per-element distortion decomposition determines the contribution towards the total distortion from an individual nonlinearity. It is useful in design optimization, symbolic simplification and nonlinear model reduction. In this thesis, a numerical distortion decomposition technique is introduced which combines the insight of traditional symbolic analysis with the numerical advantages of SPICE like simulators. The use of NTM leads to an efficient implementation. The proposed method greatly extends the size of the circuit and the complexity of the transistor model over what previous approaches could handle. For example, industry standard compact model, such as BSIM3V3 [35] was used for the first time in distortion analysis. The decomposition can be achieved at device, transistor and block level, all with device level accuracy. The theories have been implemented in a computer program and validated on examples. The proposed methods will leverage the performance of present VS based distortion analysis to the next level.

This research was done to develop tools to predict parametric roll motion of ships in regular and irregular sea and provide guidelines to avoid parametric roll during initial design stage. A post Panamax hull form (modified C11 Hull form, Courtesy of MARIN) was used to study parametric roll in ships. The approach of the study has been to simplify the roll equation of motion to a single degree of freedom equation so as to utilize the tools available to analyze the system retaining the non-linear character of the system. The Hill’ equation is used to develop highly accurate stability boundaries in the Ince-Strutt Diagram. The effect of non-linear damping has also been incorporated into the chart for the first time providing a simple method to predict the bounded roll motion amplitude. Floquet theory is also extended to predict parametric roll motion amplitude. Forward speed of the vessel has been treated as a bifurcation parameter and its effects studied both in head and following sea condition. In the second half of the research, parametric roll of the vessel in irregular sea is investigated using the Volterra Quadratic model. GM variation in irregular sea was obtained using transfer functions of the Volterra model. Heave and pitch coupling to roll motion was also studied using this approach. Sensitivity studies of spectral peak period and significant wave height on roll motion amplitude were also carried out. Forward speed effects were also evaluated using the Volterra approach. Based on the study, the Hill’s equation approach was found to give more accurate prediction of parametric roll in regular sea. The boundaries in the stability chart were more accurately defined by the Hill’s equation. The inclusion of non-linear damping in the stability chart gave reasonably accurate bounded motion amplitude prediction. The Volterra approach was found to be a good analytical prediction tool for parametric roll motion in irregular sea. Using the Volterra model, it was found that there is a high probability of parametric roll when the spectral modal period is close to twice the natural period of roll.

Digital satellite communication systems are equipped with nonlinear amplifiers such as travelling wave tube (TWT) amplifiers at or near saturation for better efficiency. The TWT exhibits nonlinear distortion in both amplitude and phase (AM/AM and AM/PM) conversion, respectively. That is, in the digital satellite communication the transmission is disturbed not only by the non-linearity of transmitter amplifier, but also by the inter-symbol interference (ISI) with additive white Gaussian noise. To compensate the non-linearity of the transmitter amplifier and ISI, in this thesis, a new nonlinear compensation scheme consists of the predistorter and adaptive third-order Volterra-based equalizer, with the inverse QRD-RLS (IQRD-RLS) algorithm, which are located before and after the nonlinear channel, is proposed respectively. The third-order Volterra filter (TVF) equalizer based on the IQRD-RLS algorithm achieve superior performance, in terms of convergence rate, steady-state mean-squared error (MSE), and numerically stable. They are highly amenable to parallel implementation using array architectures, such as systolic arrays. The computer simulation results using the M-ary PSK modulation scheme are carried out the signal¡¦s constellation diagrams, the learning curve of the MSE and the bit error rate (BER) are compared with conventional least mean square (LMS), gradient adaptive lattice (GAL) and adaptive LMS with lattice pre-filter algorithms.

The need and desire to create robust and accurate joining of materials has been one of up most importance throughout the course of history. Many forms have often been employed, but none exhibit the strength or durability as the weld. This study endeavors to explore some of the aspects of welding, more specifically relating to the Double Sided Arc Welding process and how best to model the dynamic non-linear response of such a system. Concepts of the Volterra series, NARMAX approximation and neural networks are explored. Fundamental methods of the neural network, including radial basis functions, and Back-propagation are investigated.

This research presents a complete review of signal processing techniques used, today, in vibration based industrial condition monitoring and diagnostics. It also introduces two novel techniques to this field, namely: the Kolmogorov-Smirnov test and Volterra series, which have not yet been applied to vibration based condition monitoring. The first technique, the Kolmogorov-Smirnov test, relies on a statistical comparison of the cumulative probability distribution functions (CDF) from two time series. It must be emphasised that this is not a moment technique, and it uses the whole CDF, in the comparison process. The second tool suggested in this research is the Volterra series. This is a non-linear signal processing technique, which can be used to model a time series. The parameters of this model are used for condition monitoring applications. Finally, this work also presents a comprehensive comparative study between these new methods and the existing techniques. This study is based on results from numerical and experimental applications of each technique here discussed. The concluding remarks include suggestions on how the novel techniques proposed here can be improved.

The need for high spectral efficiency and data rate drives the modulation schemes like OFDM and QAM. The resulting signal is a complex signal with high peak to average power ratio. This property causes signal sensitivity to the non-linearity of power amplifiers. Power amplifiers create out-of-band distortion, in band distortion and spectral re-growth. The spectral re-growth affects the adjacent channels and cause Adjacent Channel Interference (ACI). So linearization techniques should be used to remove the skirts produced by the amplifier in the adjacent frequencies. The objective of this thesis is to figure out a pre distortion method that is simple enough to implement with an analog circuit. We are proposing a novel method to model the non linearity and use the same model as post-distorter and pre-distorter to invert non linearity so linear gain is maintained. The implementation is generic to all the non linear systems and can be implemented to invert the non linearity of any such system.

No description available.

Orientador: João Marcos Travassos Romano / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-04T07:52:07Z (GMT). No. of bitstreams: 1 Attux_RomisRibeirodeFaissol_D.pdf: 4889703 bytes, checksum: 022efe9d9ffb4a1629612763bc2c2b3d (MD5) Previous issue date: 2005 / Resumo: O objetivo deste trabalho é investigar a aplicação de estruturas não-lineares e de técnicas de otimização baseadas em computação evolutiva a problemas de equalização e identificação de canal. O relato se divide em duas partes: a primeira voltada à análise dos fundamentos do problema de filtragem, e a segunda, à apresentação de novas abordagens para sua solução. A primeira parte, inaugurada pelas noções primordiais de comunicação, abrange os diferentes aspectos do projeto de um filtro. Permeia toda a exposição uma idéia fundamental: o estabelecimento de um paradigma genérico de filtragem adaptativa. Na segunda parte, apresentamos contribuições originais que se encaixam de diversas formas no espírito desse paradigma. Os problemas abordados são: equalização linear cega, equalização e pré-distorção baseadas em redes neurais, identificação cega, identificação de plantas recursivas, busca cega do receptor de máxima verossimilhança e equalização não-linear cega baseada em predição. Tais propostas, além de possuírem um valor intrínseco, podem ser entendidas como um corpus de evidências da validade das idéias unificadoras pertencentes ao arcabouço teórico erigido / Abstract: The objective of this work is to investigate the use of nonlinear structures and optimization techniques based on evolutionary computation in channel equalization and identification problems. The text is structured according to a twofold division: the first part is dedicated to the analysis of the foundations of the filtering problem, and the second, to the exposition of new approaches to its solution. The first part, whose starting point is the primordial idea of communication, encompasses the various aspects of the design of a signal-processing device. The entire explanation is permeated by a fundamental idea: the constitution of a generic paradigm for adaptive filtering. In the second part, a number of original contributions are presented that are related in various ways to the essence of this paradigm. These contributions involve the problems of blind linear equalization, neural network-based equalization and pre-distortion, blind and supervised identification of feedforward and feedback plants, maximum-likelihood sequence estimation and nonlinear blind equalization based on prediction. Such proposals, apart from possessing an intrinsic value, can also be understood as a corpus of evidences of the validity of the unifying ideas belonging to the established theoretical framework / Doutorado / Telecomunicações e Telemática / Doutor em Engenharia Elétrica

Volterra Series (VS) is often used in the analysis of mildly nonlinear circuits. In this approach, nonlinear circuit analysis is converted into the analysis of a series of linear circuits. The main benefit of this approach is that linear circuit analysis is well established and direct frequency domain analysis of a nonlinear circuit becomes possible. Sensitivity analysis is useful in comparing the quality of two designs and the evaluation of gradient, Jacobian or Hessian matrices, in analog Computer Aided Design. This thesis presents, for the first time, the sensitivity analysis of mildly nonlinear circuits in the frequency domain as an extension of the VS approach. To overcome efficiency limitation due to multiple mixing effects, Nonlinear Transfer Matrix (NTM) is introduced. It is the first explicit analytical representation of the complicated multiple mixing effects. The application of NTM in sensitivity analysis is capable of two orders of magnitude speedup. Per-element distortion decomposition determines the contribution towards the total distortion from an individual nonlinearity. It is useful in design optimization, symbolic simplification and nonlinear model reduction. In this thesis, a numerical distortion decomposition technique is introduced which combines the insight of traditional symbolic analysis with the numerical advantages of SPICE like simulators. The use of NTM leads to an efficient implementation. The proposed method greatly extends the size of the circuit and the complexity of the transistor model over what previous approaches could handle. For example, industry standard compact model, such as BSIM3V3 [35] was used for the first time in distortion analysis. The decomposition can be achieved at device, transistor and block level, all with device level accuracy. The theories have been implemented in a computer program and validated on examples. The proposed methods will leverage the performance of present VS based distortion analysis to the next level.