Submitted by Renata Lopes (renatasil82@gmail.com) on 2015-12-16T13:33:15Z No. of bitstreams: 1 bernardosottomaiorperalva.pdf: 8631621 bytes, checksum: e4e7f3d592c91e719474b259727bab6c (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2015-12-16T15:15:06Z (GMT) No. of bitstreams: 1 bernardosottomaiorperalva.pdf: 8631621 bytes, checksum: e4e7f3d592c91e719474b259727bab6c (MD5) / Made available in DSpace on 2015-12-16T15:15:06Z (GMT). No. of bitstreams: 1 bernardosottomaiorperalva.pdf: 8631621 bytes, checksum: e4e7f3d592c91e719474b259727bab6c (MD5) Previous issue date: 2015-09-11 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Esta tese apresenta técnicas de processamento de dados para a detecção de sinais e estimação de energia usando calorimetria de altas energias. Os calorímetros modernos possuem milhares de canais de leitura e operam sob alta taxa de eventos. Tipicamente, a reconstrução da energia envolve etapas de detecção e estimação, e é baseada na medida da amplitude do sinal (digitalizado) recebido. Os métodos empregados, atualmente, em experimentos de altas energias são baseados em técnicas de minimização da variância e selecionam os sinais de interesse a partir da estimação da energia. Este trabalho explora o uso de filtros casados para a detecção de sinais e faz uso de uma calibração para a estimação da energia dos sinais. Na abordagem proposta, os parâmetros aleatórios do pulso processado (fase e deformação) e a estatística do ruído de fundo são considerados no projeto do filtro digital, aumentando seu desempenho. No caso particular de experimentos onde a probabilidade de empilhamento de sinais é alta, uma outra solução, baseada na desconvolução linear de sinais para estimação de energia, é discutida. As técnicas propostas nesta tese foram implementadas offline e aplicadas no calorímetro de telhas (TileCal) do ATLAS no LHC. Foram utilizados sinais simulados, assim como dados reais adquiridos durante a operação nominal do LHC. Os estimadores propostos apresentaram menor erro quando comparados aos métodos empregados em calorímetros modernos e estão, atualmente, sendo validados para serem utilizados no TileCal. / This thesis presents data processing techniques of signal detection and energy estimation for high energy calorimetry. Modern calorimeters have thousands of readout channels and operate at high event rate conditions. Typically, the energy reconstruction involves both detection and estimation tasks, and it is based on the amplitude estimation of the received digitized signal. The current methods employed by high energy experiments are based on variance minimization techniques, and the valid signals are selected based on the energy estimation. This work explores the use of a technique based on Matched Filter for signal detection, and it makes use of a calibration factor to estimate the energy. In the proposed approach, the stochastic parameters of the pulse (phase and deformation) and the statistics from the background are considered for the filter design in order to increase performance. In particular cases, where the signal pile-up is likely to occur, another promising technique, based on linear signal deconvolution is discussed. The techniques proposed in this thesis were implemented offline and applied on the ATLAS Tile Calorimeter (TileCal) at LHC. Both simulated signals and real data acquired during nominal LHC operation were used. The proposed estimators presented smaller error with respect to the methods currently used in modern calorimeter systems, and they have been extensively tested to be used in TileCal.

This thesis deals with the demonstration of bit error rate reduction techniques. In the theory section, different techniques of bit error rate reduction are presented, followed by the introduction of the communication channel and the communication system parameters. Each technique is simulated in Matlab Simulink environment using the additive white Gaussian noise channel model. The simulations are captured in waveform oscillograms of all the signal processing stages. The practical section of this thesis offers a functional laboratory solution demonstrating different ways of transmission: a direct-path signal, a path with a cross-correlation receiver and a path using matched filtering. The individual circuits are described in detail, including waveform oscillograms of the signal processing blocks for illustration. Furthermore, the practical section presents printed circuit boards designs, comprehensive documentation for production, measurement results and a sample laboratory protocol.

No description available.

Este trabalho descreve o desenvolvimento de um algoritmo para avaliar o grau de corrosão em paredes de oleodutos, através de ultrassom. O algoritmo desenvolvido será implementado em um circuito digital, fazendo parte de um sistema que poderá ser embarcado em pigs ultrassônicos para inspeção de dutos à procura de corrosão. O modelo matemático conhecido como filtro casado é usado como base do algoritmo, além de um método de detecção de picos para localização dos sinais de eco de ultrassom, provenientes das reflexões do sinal nas paredes dos dutos. Um dos problemas é a definição do sinal (e do filtro) que será utilizado, mas por meio de sinais sintetizados (signal design) uma grande gama de alternativas foi analisada e apenas algumas foram selecionadas para testes em experimentos. Por último os melhores sinais foram utilizados na inspeção de um corpo de prova feito à partir de um duto corroído, e os resultados são analisados. A detecção da primeira parede do oleoduto apresenta resultados promissores em comparação com a medição tridimensional das mesmas paredes. O sistema foi capaz de reconstruir o perfil da parede interna do duto com elevada verossimilhança, mesmo em regiões severamente corroídas. A detecção da segunda parede apresenta resultados satisfatórios para baixos níveis de corrosão, porém alguns problemas foram encontrados para níveis mais altos de corrosão, prejudicando a medição direta da espessura da parede nestas condições. / This work describes the development of an algorithm to evaluate the degree of corrosion in pipeline walls, using ultrasound. The developed algorithm will be implemented in a dedicated digital circuit that can be embedded in ultrasonic pigs for pipeline corrosion inspection. The algorithm is based on the mathematic model known as matched filter, besides a peak detection method for the location of ultrasound echoes, originated from the signal reflections in the pipeline walls. One problem is the determination of the signal (and filter) that should be used, but using a signal design approach a large number of possibilities could be analyzed and only a few was tested in experiments. Finally, the best signals were used to inspect a test specimen made of a corroded pipeline section, and the results were analyzed. The first wall detection shows promising results when compared to the results of a three-dimensional inspection of the same walls. It was possible to reconstruct the profile of the internal wall with good likelihood, even at badly corroded areas. The second wall detection shows some satisfactory results on low corrosion levels, but show some problems with high corrosion levels, compromising the direct measurement of the wall of the pipeline.

Este trabalho descreve o desenvolvimento de um algoritmo para avaliar o grau de corrosão em paredes de oleodutos, através de ultrassom. O algoritmo desenvolvido será implementado em um circuito digital, fazendo parte de um sistema que poderá ser embarcado em pigs ultrassônicos para inspeção de dutos à procura de corrosão. O modelo matemático conhecido como filtro casado é usado como base do algoritmo, além de um método de detecção de picos para localização dos sinais de eco de ultrassom, provenientes das reflexões do sinal nas paredes dos dutos. Um dos problemas é a definição do sinal (e do filtro) que será utilizado, mas por meio de sinais sintetizados (signal design) uma grande gama de alternativas foi analisada e apenas algumas foram selecionadas para testes em experimentos. Por último os melhores sinais foram utilizados na inspeção de um corpo de prova feito à partir de um duto corroído, e os resultados são analisados. A detecção da primeira parede do oleoduto apresenta resultados promissores em comparação com a medição tridimensional das mesmas paredes. O sistema foi capaz de reconstruir o perfil da parede interna do duto com elevada verossimilhança, mesmo em regiões severamente corroídas. A detecção da segunda parede apresenta resultados satisfatórios para baixos níveis de corrosão, porém alguns problemas foram encontrados para níveis mais altos de corrosão, prejudicando a medição direta da espessura da parede nestas condições. / This work describes the development of an algorithm to evaluate the degree of corrosion in pipeline walls, using ultrasound. The developed algorithm will be implemented in a dedicated digital circuit that can be embedded in ultrasonic pigs for pipeline corrosion inspection. The algorithm is based on the mathematic model known as matched filter, besides a peak detection method for the location of ultrasound echoes, originated from the signal reflections in the pipeline walls. One problem is the determination of the signal (and filter) that should be used, but using a signal design approach a large number of possibilities could be analyzed and only a few was tested in experiments. Finally, the best signals were used to inspect a test specimen made of a corroded pipeline section, and the results were analyzed. The first wall detection shows promising results when compared to the results of a three-dimensional inspection of the same walls. It was possible to reconstruct the profile of the internal wall with good likelihood, even at badly corroded areas. The second wall detection shows some satisfactory results on low corrosion levels, but show some problems with high corrosion levels, compromising the direct measurement of the wall of the pipeline.

<p>Signal processing within the neurophysiological field is challenging and requires short processing time and reliable results. In this thesis, three main problems are considered.</p><p>First, a modified line source model for simulation of muscle action potentials (APs) is presented. It is formulated in continuous-time as a convolution of a muscle-fiber dependent transmembrane current and an electrode dependent weighting (impedance) function. In the discretization of the model, the Nyquist criterion is addressed. By applying anti-aliasing filtering, it is possible to decrease the discretization frequency while retaining the accuracy. Finite length muscle fibers are incorporated in the model through a simple transformation of the weighting function. The presented model is suitable for modeling large motor units.</p><p>Second, the possibility of discerning the individual AP components of the concentric needle electromyogram (EMG) is explored. Simulated motor unit APs (MUAPs) are prefiltered using Wiener filtering. The mean fiber concentration (MFC) and jitter are estimated from the prefiltered MUAPs. The results indicate that the assessment of the MFC may well benefit from the presented approach and that the jitter may be estimated from the concentric needle EMG with an accuracy comparable with traditional single fiber EMG.</p><p>Third, automatic, rather than manual, detection and discrimination of recorded C-fiber APs is addressed. The algorithm, detects the Aps reliably using a matched filter. Then, the detected APs are discriminated using multiple hypothesis tracking combined with Kalman filtering which identifies the APs originating from the same C-fiber. To improve the performance, an amplitude estimate is incorporated into the tracking algorithm. Several years of use show that the performance of the algorithm is excellent with minimal need for audit.</p>

Signal processing within the neurophysiological field is challenging and requires short processing time and reliable results. In this thesis, three main problems are considered. First, a modified line source model for simulation of muscle action potentials (APs) is presented. It is formulated in continuous-time as a convolution of a muscle-fiber dependent transmembrane current and an electrode dependent weighting (impedance) function. In the discretization of the model, the Nyquist criterion is addressed. By applying anti-aliasing filtering, it is possible to decrease the discretization frequency while retaining the accuracy. Finite length muscle fibers are incorporated in the model through a simple transformation of the weighting function. The presented model is suitable for modeling large motor units. Second, the possibility of discerning the individual AP components of the concentric needle electromyogram (EMG) is explored. Simulated motor unit APs (MUAPs) are prefiltered using Wiener filtering. The mean fiber concentration (MFC) and jitter are estimated from the prefiltered MUAPs. The results indicate that the assessment of the MFC may well benefit from the presented approach and that the jitter may be estimated from the concentric needle EMG with an accuracy comparable with traditional single fiber EMG. Third, automatic, rather than manual, detection and discrimination of recorded C-fiber APs is addressed. The algorithm, detects the Aps reliably using a matched filter. Then, the detected APs are discriminated using multiple hypothesis tracking combined with Kalman filtering which identifies the APs originating from the same C-fiber. To improve the performance, an amplitude estimate is incorporated into the tracking algorithm. Several years of use show that the performance of the algorithm is excellent with minimal need for audit.

In wireless networks, reliable communication is a challenging issue due to many attenuation factors such as receiver noise, channel fading, interference and asynchronous delays. Lattice coding and decoding provide efficient solutions to many problems in wireless communications and multiuser information theory. The capability in achieving the fundamental limits, together with simple and efficient transmitter and receiver structures, make the lattice strategy a promising approach. This work deals with problems of lattice detection over fading channels and time asynchronism over the lattice-based compute-and-forward protocol. In multiple-input multiple-output (MIMO) systems, the use of lattice reduction significantly improves the performance of approximate detection techniques. In the first part of this thesis, by taking advantage of the temporal correlation of a Rayleigh fading channel, low complexity lattice reduction methods are investigated. We show that updating the reduced lattice basis adaptively with a careful use of previous channel realizations yields a significant saving in complexity with a minimal degradation in performance. Considering high data rate MIMO systems, we then investigate soft-output detection methods. Using the list sphere decoder (LSD) algorithm, an adaptive method is proposed to reduce the complexity of generating the list for evaluating the log-likelihood ratio (LLR) values. In the second part, by applying the lattice coding and decoding schemes over asynchronous networks, we study the impact of asynchronism on the compute-and-forward strategy. While the key idea in compute-and-forward is to decode a linear synchronous combination of transmitted codewords, the distributed relays receive random asynchronous versions of the combinations. Assuming different asynchronous models, we design the receiver structure prior to the decoder of compute-and-forward so that the achievable rates are maximized at any signal-to-noise-ratio (SNR). Finally, we consider symbol-asynchronous X networks with single antenna nodes over time-invariant channels. We exploit the asynchronism among the received signals in order to design the interference alignment scheme. It is shown that the asynchronism provides correlated channel variations which are proved to be sufficient to implement the vector interference alignment over the constant X network.

There has recently been growing interest in using physical layer network coding techniques to facilitate information transfer in wireless relay networks. The physical layer network coding technique takes advantage of the additive nature of wireless signals by allowing two terminals to transmit simultaneously to the relay node. This technique has several performance benefits, such as improving utilization and throughput of wireless channels and reducing delay. In this thesis, we present an algorithm for joint decoding of two unsynchronized transmitters to a modulo-2 sum of their transmitted messages. We address the problems that arise when the boundaries of the signals do not align with each other and when their phases are not identical. Our approach uses a state-based Viterbi decoding scheme that takes into account the timing offsets between the interfering signals. As a future research plan, we plan to utilize software-defined radios (SDRs) as a testbed to show the practicality of our approach and to verify its performance. Our simulation studies show that the decoder performs well with the only degrading factor being the noise level in the channel.

Multiple-input multiple-output (MIMO) radars, which utilize multiple transmitters and receivers to send and receive independent waveforms, have been actively investigated as a next generation radar technology inspired by MIMO techniques in communication theory. Complementary metal-oxide-semiconductor (CMOS) technology offers an opportunity for dramatic cost and size reduction for a MIMO array. However, the resulting formidable signal processing burden has not been addressed properly and remains a challenge. On the other hand, from a block-level point of view, an analog-to-digital converter (ADC) is required for mixed-signal processing to convert analog signals to digital signals, but an ADC occupies a significant portion of a system's budget. Therefore, improvement of an ADC will greatly enhance various trade-offs. This research presents an alternative and viable approach for a MIMO array from a system architecture point of view, and also develops circuit level improvement techniques for an ADC. This dissertation presents a fully-integrated analog pulse compressor (APC) based on an analog matched filter in a mixed signal domain as a key block for the waveform diversity MIMO radar. The performance gain of the proposed system is mathematically presented, and the proposed system is successfully implemented and demonstrated from the block level to the system level using various waveforms. Various figures of merit are proposed to aid system evaluations. This dissertation also presents a low-power ADC based on an asynchronous sample-and-hold multiplying SAR (ASHMSAR) with an enhanced input range dynamic comparator as a key element of a future system. Overall, with the new ADC, a high level of system performance without severe penalty on power consumption is expected. The research in this dissertation provides low-cost and low-power MIMO solutions for a future system by addressing both system issues and circuit issues comprehensively.