26 resultados para discrete wavelet transform

em Instituto Polit


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We introduce a new wavelet transform within the framework of the local fractional calculus. An illustrative example of local fractional wavelet transform is also presented.

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In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.

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In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.

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Mestrado em Engenharia Electrotécnica e de Computadores

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Stock market indices SMIs are important measures of financial and economical performance. Considerable research efforts during the last years demonstrated that these signals have a chaotic nature and require sophisticated mathematical tools for analyzing their characteristics. Classical methods, such as the Fourier transform, reveal considerable limitations in discriminating different periods of time. This paper studies the dynamics of SMI by combining the wavelet transform and the multidimensional scaling MDS . Six continuous wavelets are tested for analyzing the information content of the stock signals. In a first phase, the real Shannon wavelet is adopted for performing the evaluation of the SMI dynamics, while their comparison is visualized by means of the MDS. In a second phase, the other wavelets are also tested, and the corresponding MDS plots are analyzed.

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This paper presents the measurement, frequency-response modeling and identification, and the corresponding impulse time response of the human respiratory impedance and admittance. The investigated adult patient groups were healthy, diagnosed with chronic obstructive pulmonary disease and kyphoscoliosis, respectively. The investigated children patient groups were healthy, diagnosed with asthma and cystic fibrosis, respectively. Fractional order (FO) models are identified on the measured impedance to quantify the respiratory mechanical properties. Two methods are presented for obtaining and simulating the time-domain impulse response from FO models of the respiratory admittance: (i) the classical pole-zero interpolation proposed by Oustaloup in the early 90s, and (ii) the inverse discrete Fourier Transform (DFT). The results of the identified FO models for the respiratory admittance are presented by means of their average values for each group of patients. Consequently, the impulse time response calculated from the frequency response of the averaged FO models is given by means of the two methods mentioned above. Our results indicate that both methods provide similar impulse response data. However, we suggest that the inverse DFT is a more suitable alternative to the high order transfer functions obtained using the classical Oustaloup filter. Additionally, a power law model is fitted on the impulse response data, emphasizing the intrinsic fractal dynamics of the respiratory system.

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Ao longo dos últimos anos, acompanhada da evolução tecnológica, da dificuldade da inspeção visual e da consciencialização dos efeitos de uma má inspeção, verificou-se uma maior sensibilidade para a importância da monitorização estrutural, principalmente nas grandes infra-estruturas de engenharia civil. Os sistemas de monitorização estrutural permitem o acompanhamento contínuo do comportamento de uma determinada estrutura de tal forma que com os dados obtidos, é possível avaliar alterações no comportamento da mesma. Com isso, tem-se desenvolvido e implementado estratégias de identificação de danos estruturais com o intuito de aumentar a fiabilidade estrutural e evitar precocemente que alterações na condição da estrutura possam evoluir para situações mais severas. Neste contexto, a primeira parte desta dissertação consiste numa introdução à monitorização estrutural e à deteção de dano estrutural. Relativamente à monitorização, são expostos os seus objetivos e os princípios da sua aplicação. Conjuntamente são apresentados e descritos os principais sensores e são explicadas as funcionalidades de um sistema de aquisição de dados. O segundo tema aborda a importância da deteção de dano introduzindo os métodos estudados neste trabalho. Destaca-se o método das linhas de influência, o método da curvatura dos modos de vibração e o método da transformada de wavelet. Na segunda parte desta dissertação são apresentados dois casos de estudo. O primeiro estudo apresenta uma componente numérica e uma componente experimental. Estuda-se um modelo de viga que se encontra submetida a vários cenários de dano e valida-se a capacidade do método das linhas de influência em detetar e localizar essas anomalias. O segundo estudo consiste na modelação numérica de uma ponte real, na posterior simulação de cenários de dano e na análise comparativa da eficácia de cada um dos três métodos de deteção de dano na identificação e localização dos danos simulados. Por último, são apresentadas as principais conclusões deste trabalho e são sugeridos alguns tópicos a explorar na elaboração de trabalhos futuros.

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This paper studies the human DNA in the perspective of signal processing. Six wavelets are tested for analyzing the information content of the human DNA. By adopting real Shannon wavelet several fundamental properties of the code are revealed. A quantitative comparison of the chromosomes and visualization through multidimensional and dendograms is developed.

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This technical report describes the work carried out in a project within the ERASMUS programme. The objective of this project was the Integration of an Automatic Warehouse in a Discrete-Part Automation System. The discrete-part automation system located at the LASCRI (Critical Systems) laboratory at ISEP was extended with automatic storage and retrieval of the manufacturing parts, through the integration of an automatic warehouse and an automatic guided vehicle (AGV).

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The goal of this study is to analyze the dynamical properties of financial data series from nineteen worldwide stock market indices (SMI) during the period 1995–2009. SMI reveal a complex behavior that can be explored since it is available a considerable volume of data. In this paper is applied the window Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional order systems.

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Optimization problems arise in science, engineering, economy, etc. and we need to find the best solutions for each reality. The methods used to solve these problems depend on several factors, including the amount and type of accessible information, the available algorithms for solving them, and, obviously, the intrinsic characteristics of the problem. There are many kinds of optimization problems and, consequently, many kinds of methods to solve them. When the involved functions are nonlinear and their derivatives are not known or are very difficult to calculate, these methods are more rare. These kinds of functions are frequently called black box functions. To solve such problems without constraints (unconstrained optimization), we can use direct search methods. These methods do not require any derivatives or approximations of them. But when the problem has constraints (nonlinear programming problems) and, additionally, the constraint functions are black box functions, it is much more difficult to find the most appropriate method. Penalty methods can then be used. They transform the original problem into a sequence of other problems, derived from the initial, all without constraints. Then this sequence of problems (without constraints) can be solved using the methods available for unconstrained optimization. In this chapter, we present a classification of some of the existing penalty methods and describe some of their assumptions and limitations. These methods allow the solving of optimization problems with continuous, discrete, and mixing constraints, without requiring continuity, differentiability, or convexity. Thus, penalty methods can be used as the first step in the resolution of constrained problems, by means of methods that typically are used by unconstrained problems. We also discuss a new class of penalty methods for nonlinear optimization, which adjust the penalty parameter dynamically.

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The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indexes during the period 2000–2009. We analyze, under a regional criterium, ten main indexes at a daily time horizon. The methods and algorithms that have been explored for the description of dynamical phenomena become an effective background in the analysis of economical data. We start by applying the classical concepts of signal analysis, fractional Fourier transform, and methods of fractional calculus. In a second phase we adopt the multidimensional scaling approach. Stock market indexes are examples of complex interacting systems for which a huge amount of data exists. Therefore, these indexes, viewed from a different perspectives, lead to new classification patterns.

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This study addresses the optimization of rational fraction approximations for the discrete-time calculation of fractional derivatives. The article starts by analyzing the standard techniques based on Taylor series and Padé expansions. In a second phase the paper re-evaluates the problem in an optimization perspective by tacking advantage of the flexibility of the genetic algorithms.

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A genetic algorithm used to design radio-frequency binary-weighted differential switched capacitor arrays (RFDSCAs) is presented in this article. The algorithm provides a set of circuits all having the same maximum performance. This article also describes the design, implementation, and measurements results of a 0.25 lm BiCMOS 3-bit RFDSCA. The experimental results show that the circuit presents the expected performance up to 40 GHz. The similarity between the evolutionary solutions, circuit simulations, and measured results indicates that the genetic synthesis method is a very useful tool for designing optimum performance RFDSCAs.

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The paper presents a RFDSCA automated synthesis procedure. This algorithm determines several RFDSCA circuits from the top-level system specifications all with the same maximum performance. The genetic synthesis tool optimizes a fitness function proportional to the RFDSCA quality factor and uses the epsiv-concept and maximin sorting scheme to achieve a set of solutions well distributed along a non-dominated front. To confirm the results of the algorithm, three RFDSCAs were simulated in SpectreRF and one of them was implemented and tested. The design used a 0.25 mum BiCMOS process. All the results (synthesized, simulated and measured) are very close, which indicate that the genetic synthesis method is a very useful tool to design optimum performance RFDSCAs.