Many emerging applications call for wideband analog-to-digital converters and some require medium-to-high resolution. Incorporating such ADCs allows for shifting as much of the signal processing tasks as possible to the digital domain, where more flexible and programmable circuits are available. However, realizing such ADCs with the existing single stage architectures is very challenging. Therefore, parallel ADC architectures such as time-interleaved structures are used. Unfortunately, such architectures require high-speed high-precision sample-and-hold (S/H) stages that are challenging to implement. In this thesis, a parallel ADC architecture, namely, the frequency-translating hybrid ADC (FTH-ADC) is proposed to increase the conversion speed of the ADCs, which is also suitable for applications requiring medium-to-high resolution ADCs. This architecture addresses the sampling problem by sampling on narrowband baseband subchannels, i.e., sampling is accomplished after splitting the wideband input signals into narrower subbands and frequency-translating them into baseband where identical narrowband baseband S/Hs can be used. Therefore, lower-speed, lower-precision S/Hs are required and single-chip CMOS implementation of the entire ADC is possible. A proof of concept board-level implementation of the FTH-ADC is used to analyze the effects of major analog non-idealities and errors. Error measurement and compensation methods are presented. Using four 8-bit, 100 MHz subband ADCs, four 25 MHz Butterworth filters, two 64-tap FIR reconstruction filters, and four 10-tap FIR compensation filters, a total system with an effective sample rate of 200 MHz is implemented with an effective number of bits of at least 7 bits over the entire 100 MHz input bandwidth. In addition, one path of an 8-GHz, 4-bit, FTH-ADC system, including a highly-linear mixer and a 5th-order, 1 GHz, Butterworth Gm-C filter, is implemented in a 90 nm CMOS technology. Followed by a 4-bit, 4-GHz subband ADC, the blocks consume a total power of 52 mW from a 1.2 V supply, and occupy an area of 0.05 mm2. The mixer-filter has a THD ≤ 5% (26 dB) over its full 1 GHz bandwidth and provides a signal with a voltage swing of 350 mVpp for the subsequent ADC stage.

Many emerging applications call for wideband analog-to-digital converters and some require medium-to-high resolution. Incorporating such ADCs allows for shifting as much of the signal processing tasks as possible to the digital domain, where more flexible and programmable circuits are available. However, realizing such ADCs with the existing single stage architectures is very challenging. Therefore, parallel ADC architectures such as time-interleaved structures are used. Unfortunately, such architectures require high-speed high-precision sample-and-hold (S/H) stages that are challenging to implement. In this thesis, a parallel ADC architecture, namely, the frequency-translating hybrid ADC (FTH-ADC) is proposed to increase the conversion speed of the ADCs, which is also suitable for applications requiring medium-to-high resolution ADCs. This architecture addresses the sampling problem by sampling on narrowband baseband subchannels, i.e., sampling is accomplished after splitting the wideband input signals into narrower subbands and frequency-translating them into baseband where identical narrowband baseband S/Hs can be used. Therefore, lower-speed, lower-precision S/Hs are required and single-chip CMOS implementation of the entire ADC is possible. A proof of concept board-level implementation of the FTH-ADC is used to analyze the effects of major analog non-idealities and errors. Error measurement and compensation methods are presented. Using four 8-bit, 100 MHz subband ADCs, four 25 MHz Butterworth filters, two 64-tap FIR reconstruction filters, and four 10-tap FIR compensation filters, a total system with an effective sample rate of 200 MHz is implemented with an effective number of bits of at least 7 bits over the entire 100 MHz input bandwidth. In addition, one path of an 8-GHz, 4-bit, FTH-ADC system, including a highly-linear mixer and a 5th-order, 1 GHz, Butterworth Gm-C filter, is implemented in a 90 nm CMOS technology. Followed by a 4-bit, 4-GHz subband ADC, the blocks consume a total power of 52 mW from a 1.2 V supply, and occupy an area of 0.05 mm2. The mixer-filter has a THD ≤ 5% (26 dB) over its full 1 GHz bandwidth and provides a signal with a voltage swing of 350 mVpp for the subsequent ADC stage.

Many emerging applications call for wideband analog-to-digital converters and some require medium-to-high resolution. Incorporating such ADCs allows for shifting as much of the signal processing tasks as possible to the digital domain, where more flexible and programmable circuits are available. However, realizing such ADCs with the existing single stage architectures is very challenging. Therefore, parallel ADC architectures such as time-interleaved structures are used. Unfortunately, such architectures require high-speed high-precision sample-and-hold (S/H) stages that are challenging to implement. In this thesis, a parallel ADC architecture, namely, the frequency-translating hybrid ADC (FTH-ADC) is proposed to increase the conversion speed of the ADCs, which is also suitable for applications requiring medium-to-high resolution ADCs. This architecture addresses the sampling problem by sampling on narrowband baseband subchannels, i.e., sampling is accomplished after splitting the wideband input signals into narrower subbands and frequency-translating them into baseband where identical narrowband baseband S/Hs can be used. Therefore, lower-speed, lower-precision S/Hs are required and single-chip CMOS implementation of the entire ADC is possible. A proof of concept board-level implementation of the FTH-ADC is used to analyze the effects of major analog non-idealities and errors. Error measurement and compensation methods are presented. Using four 8-bit, 100 MHz subband ADCs, four 25 MHz Butterworth filters, two 64-tap FIR reconstruction filters, and four 10-tap FIR compensation filters, a total system with an effective sample rate of 200 MHz is implemented with an effective number of bits of at least 7 bits over the entire 100 MHz input bandwidth. In addition, one path of an 8-GHz, 4-bit, FTH-ADC system, including a highly-linear mixer and a 5th-order, 1 GHz, Butterworth Gm-C filter, is implemented in a 90 nm CMOS technology. Followed by a 4-bit, 4-GHz subband ADC, the blocks consume a total power of 52 mW from a 1.2 V supply, and occupy an area of 0.05 mm2. The mixer-filter has a THD ≤ 5% (26 dB) over its full 1 GHz bandwidth and provides a signal with a voltage swing of 350 mVpp for the subsequent ADC stage. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

nÃo hà / A modernizaÃÃo de processos tem aumentado o emprego de cargas com caracterÃstica fortemente nÃo linear. Tal situaÃÃo està levando os engenheiros a uma revisÃo dos conceitos de eficiÃncia energÃtica e qualidade de energia, com o intuito de conciliar essas duas definiÃÃes. Surge, entÃo, o conceito de condicionamento de potÃncia intrÃnseco ao de qualidade de energia. Com este conceito sÃo desenvolvidas soluÃÃes que visam atender caracterÃsticas como compensaÃÃo de harmÃnicos e correÃÃo do fator de potÃncia, de maneira a garantir um sistema elÃtrico que proporcione condiÃÃes para a mÃxima eficiÃncia energÃtica de cargas conectadas à rede. Surgem, entÃo, os filtros passivos e ativos como as soluÃÃes mais comuns, tanto na prÃtica quanto na literatura tÃcnica e cientÃfica, apresentando entre si as suas vantagens e desvantagens. Buscando usufruir das vantagens de ambas as soluÃÃes, este trabalho propÃe o estudo e projeto de um filtro hÃbrido. A estrutura do filtro hÃbrido de dupla sintonia proposto permite ao mesmo a dissociaÃÃo da malha ativa de sua malha passiva, dando ao filtro maior autonomia e praticidade durante operaÃÃes de troca ou manutenÃÃo no estÃgio ativo. Este trabalho tambÃm apresenta uma metodologia para o projeto da malha passiva, bem como a modelagem e controle da malha ativa do filtro. Por se tratar de uma estrutura hÃbrida nova, sÃo realizados ensaios comparativos entre o filtro hÃbrido proposto e o filtro hÃbrido emph{shunt}, com conversor em sÃrie com o filtro passivo, a fim de validar o desempenho e a baixa potÃncia nominal da malha ativa em relaÃÃo à potÃncia do transformador ao qual serà conectado. AtravÃs da modelagem e dimensionamento do filtro hÃbrido proposto, foram obtidos, a partir de um estudo de caso, resultados satisfatÃrios quanto a correÃÃo do fator de potÃncia e minimizaÃÃo das distorÃÃes harmÃnicas de corrente e tensÃo frente as normas tÃcnicas vigentes. Tais resultados validaram o filtro hÃbrido como uma soluÃÃo tecnicamente viÃvel para a melhoria da qualidade de energia de um sistema de distribuiÃÃo em baixa tensÃo. / The modernization process has increased the use of loads with strongly non-linear characteristic. This situation is leading engineers to review the concepts of energy efficiency and power quality, in order to conciliate these two definitions. Then, the concept of power conditioning intrinsic to the power quality appears to be an interesting solution. With this concept, the solutions are designed to meet characteristics such as harmonics compensation and power factor correction, in order to ensure an electrical system that provides conditions for maximum energy efficiency of loads connected to the grid. Then arise passive filters and active as the most common solutions, both in practice and in the scientific and technical literature, with each other their advantages and disadvantages. Seeking to benefit from the advantages of both solutions, this work proposes the study and design of a hybrid filter. The proposed structure named dual tune hybrid filter allows the dissociation of the active stage from the passive stage, giving greater autonomy and practicality to the filter during replacement or maintenance operations in the active stage. This work also proposes a design methodology for the passive power stage, as well as the modeling and control of the active filter power stage. Because it is a new hybrid structure, it is made comparative analysis between the proposed hybrid power filter and shunt hybrid power filter, with the series converter with the passive filter, in order to validate the performance and its lower rated for the active stage with respect to the transformer in which it will be connected. Through modeling and design of the proposed hybrid filter, were obtained from a test case, satisfactory results as the correction of power factor and minimizing harmonic distortion voltage and current forward technical standards existing. These results validate the hybrid filter as an economically viable solution for improving the power quality of a distribution system at low voltage.

[ES] La visión artificial es uno de los campos en mayor crecimiento en la actualidad que, junto con otras tecnologías como la Biometría o el Big Data, se ha convertido en el foco de interés de numerosas investigaciones y es considerada como una de las tecnologías del futuro. Este amplio campo abarca diversos métodos entre los que se encuentra el procesamiento y análisis de imágenes digitales. El éxito del análisis de imágenes y otras tareas de procesamiento de alto nivel, como pueden ser el reconocimiento de patrones o la visión 3D, dependerá en gran medida de la buena calidad de las imágenes de partida. Hoy en día existen multitud de factores que dañan las imágenes dificultando la obtención de imágenes de calidad óptima, esto ha convertido el (pre-) procesamiento digital de imágenes en un paso fundamental previo a la aplicación de cualquier otra tarea de procesado. Los factores más comunes son el ruido y las malas condiciones de adquisición: los artefactos provocados por el ruido dificultan la interpretación adecuada de la imagen y la adquisición en condiciones de iluminación o exposición deficientes, como escenas dinámicas, causan pérdida de información de la imagen que puede ser clave para ciertas tareas de procesamiento. Los pasos de (pre-)procesamiento de imágenes conocidos como suavizado y realce se aplican comúnmente para solventar estos problemas: El suavizado tiene por objeto reducir el ruido mientras que el realce se centra en mejorar o recuperar la información imprecisa o dañada. Con estos métodos conseguimos reparar información de los detalles y bordes de la imagen con una nitidez insuficiente o un contenido borroso que impide el (post-)procesamiento óptimo de la imagen. Existen numerosos métodos que suavizan el ruido de una imagen, sin embargo, en muchos casos el proceso de filtrado provoca emborronamiento en los bordes y detalles de la imagen. De igual manera podemos encontrar una enorme cantidad de técnicas de realce que intentan combatir las pérdidas de información, sin embargo, estas técnicas no contemplan la existencia de ruido en la imagen que procesan: ante una imagen ruidosa, cualquier técnica de realce provocará también un aumento del ruido. Aunque la idea intuitiva para solucionar este último caso será el previo filtrado y posterior realce, este enfoque ha demostrado no ser óptimo: el filtrado podrá eliminar información que, a su vez, podría no ser recuperable en el siguiente paso de realce. En la presente tesis doctoral se propone un modelo basado en teoría de grafos para el procesamiento de imágenes en color. En este modelo, se construye un grafo para cada píxel de tal manera que sus propiedades permiten caracterizar y clasificar dicho pixel. Como veremos, el modelo propuesto es robusto y capaz de adaptarse a una gran variedad de aplicaciones. En particular, aplicamos el modelo para crear nuevas soluciones a los dos problemas fundamentales del procesamiento de imágenes: suavizado y realce. Se ha estudiado el modelo en profundidad en función del umbral, parámetro clave que asegura la correcta clasificación de los píxeles de la imagen. Además, también se han estudiado las posibles características y posibilidades del modelo que nos han permitido sacarle el máximo partido en cada una de las posibles aplicaciones. Basado en este modelo se ha diseñado un filtro adaptativo capaz de eliminar ruido gaussiano de una imagen sin difuminar los bordes ni perder información de los detalles. Además, también ha permitido desarrollar un método capaz de realzar los bordes y detalles de una imagen al mismo tiempo que se suaviza el ruido presente en la misma. Esta aplicación simultánea consigue combinar dos operaciones opuestas por definición y superar así los inconvenientes presentados por el enfoque en dos etapas. / [CA] La visió artificial és un dels camps en major creixement en l'actualitat que, junt amb altres tecnlogies com la Biometria o el Big Data, s'ha convertit en el focus d'interés de nombroses investigacions i és considerada com una de les tecnologies del futur. Aquest ampli camp comprén diversos m`etodes entre els quals es troba el processament digital d'imatges i anàlisis d'imatges digitals. L'èxit de l'anàlisis d'imatges i altres tasques de processament d'alt nivell, com poden ser el reconeixement de patrons o la visió 3D, dependrà en gran manera de la bona qualitat de les imatges de partida. Avui dia existeixen multitud de factors que danyen les imatges dificultant l'obtenció d'imatges de qualitat òptima, açò ha convertit el (pre-) processament digital d'imatges en un pas fonamental previa la l'aplicació de qualsevol altra tasca de processament. Els factors més comuns són el soroll i les males condicions d'adquisició: els artefactes provocats pel soroll dificulten la inter- pretació adequada de la imatge i l'adquisició en condicions d'il·luminació o exposició deficients, com a escenes dinàmiques, causen pèrdua d'informació de la imatge que pot ser clau per a certes tasques de processament. Els passos de (pre-) processament d'imatges coneguts com suavitzat i realç s'apliquen comunament per a resoldre aquests problemes: El suavitzat té com a objecte reduir el soroll mentres que el real se centra a millorar o recuperar la informació imprecisa o danyada. Amb aquests mètodes aconseguim reparar informació dels detalls i bords de la imatge amb una nitidesa insuficient o un contingut borrós que impedeix el (post-)processament òptim de la imatge. Existeixen nombrosos mètodes que suavitzen el soroll d'una imatge, no obstant això, en molts casos el procés de filtrat provoca emborronamiento en els bords i detalls de la imatge. De la mateixa manera podem trobar una enorme quantitat de tècniques de realç que intenten combatre les pèrdues d'informació, no obstant això, aquestes tècniques no contemplen l'existència de soroll en la imatge que processen: davant d'una image sorollosa, qualsevol tècnica de realç provocarà també un augment del soroll. Encara que la idea intuïtiva per a solucionar aquest últim cas seria el previ filtrat i posterior realç, aquest enfocament ha demostrat no ser òptim: el filtrat podria eliminar informació que, al seu torn, podria no ser recuperable en el seguënt pas de realç. En la present Tesi doctoral es proposa un model basat en teoria de grafs per al processament d'imatges en color. En aquest model, es construïx un graf per a cada píxel de tal manera que les seues propietats permeten caracteritzar i classificar el píxel en quëstió. Com veurem, el model proposat és robust i capaç d'adaptar-se a una gran varietat d'aplicacions. En particular, apliquem el model per a crear noves solucions als dos problemes fonamentals del processament d'imatges: suavitzat i realç. S'ha estudiat el model en profunditat en funció del llindar, paràmetre clau que assegura la correcta classificació dels píxels de la imatge. A més, també s'han estudiat les possibles característiques i possibilitats del model que ens han permés traure-li el màxim partit en cadascuna de les possibles aplicacions. Basat en aquest model s'ha dissenyat un filtre adaptatiu capaç d'eliminar soroll gaussià d'una imatge sense difuminar els bords ni perdre informació dels detalls. A més, també ha permés desenvolupar un mètode capaç de realçar els bords i detalls d'una imatge al mateix temps que se suavitza el soroll present en la mateixa. Aquesta aplicació simultània aconseguix combinar dues operacions oposades per definició i superar així els inconvenients presentats per l'enfocament en dues etapes. / [EN] Computer vision is one of the fastest growing fields at present which, along with other technologies such as Biometrics or Big Data, has become the focus of interest of many research projects and it is considered one of the technologies of the future. This broad field includes a plethora of digital image processing and analysis tasks. To guarantee the success of image analysis and other high-level processing tasks as 3D imaging or pattern recognition, it is critical to improve the quality of the raw images acquired. Nowadays all images are affected by different factors that hinder the achievement of optimal image quality, making digital image processing a fundamental step prior to the application of any other practical application. The most common of these factors are noise and poor acquisition conditions: noise artefacts hamper proper image interpretation of the image; and acquisition in poor lighting or exposure conditions, such as dynamic scenes, causes loss of image information that can be key for certain processing tasks. Image (pre-) processing steps known as smoothing and sharpening are commonly applied to overcome these inconveniences: Smoothing is aimed at reducing noise and sharpening at improving or recovering imprecise or damaged information of image details and edges with insufficient sharpness or blurred content that prevents optimal image (post-)processing. There are many methods for smoothing the noise in an image, however in many cases the filtering process causes blurring at the edges and details of the image. Besides, there are also many sharpening techniques, which try to combat the loss of information due to blurring of image texture and need to contemplate the existence of noise in the image they process. When dealing with a noisy image, any sharpening technique may amplify the noise. Although the intuitive idea to solve this last case would be the previous filtering and later sharpening, this approach has proved not to be optimal: the filtering could remove information that, in turn, may not be recoverable in the later sharpening step. In the present PhD dissertation we propose a model based on graph theory for color image processing from a vector approach. In this model, a graph is built for each pixel in such a way that its features allow to characterize and classify the pixel. As we will show, the model we proposed is robust and versatile: potentially able to adapt to a variety of applications. In particular, we apply the model to create new solutions for the two fundamentals problems in image processing: smoothing and sharpening. To approach high performance image smoothing we use the proposed model to determine if a pixel belongs to a at region or not, taking into account the need to achieve a high-precision classification even in the presence of noise. Thus, we build an adaptive soft-switching filter by employing the pixel classification to combine the outputs from a filter with high smoothing capability and a softer one to smooth edge/detail regions. Further, another application of our model allows to use pixels characterization to successfully perform a simultaneous smoothing and sharpening of color images. In this way, we address one of the classical challenges within the image processing field. We compare all the image processing techniques proposed with other state-of-the-art methods to show that they are competitive both from an objective (numerical) and visual evaluation point of view. / Pérez Benito, C. (2019). Color Image Processing based on Graph Theory [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/123955

Cette thèse est le fruit d'un partenariat entre la BL TVFE de NXP Semiconductors et l'ESIEE dans le cadre d'une thèse CIFRE. Le but est d'apporter une solution qui permette la réception de plusieurs canaux pour le câble. Ce sujet est lié à la problématique de numérisation large bande. Dans la première partie, nous faisons un état-de-l'art sur les convertisseurs analogiques-numériques (CAN), sur les architectures parallèles (entrelacement temporel et bancs de filtres hybrides (BFH)), et sur les méthodes d'échantillonnage (passe-bande et complexe). Puis, nous étudions une architecture composée d'un banc de filtres analogiques et un banc de CANs. Nous cherchons à réduire surtout le taux d'échantillonnage. Nous comparons notre solution à un CAN large bande performant, avec notre fonction de coût. L'un des avantages de cette architecture est que tous les composants sont faisables, même les CANs, et qu'il est possible d'éteindre des sous-bandes pour diminuer la consommation. Cette solution est intéressante pour le moment mais n'est pas compétitive en termes de consommation et de surface. Nous proposons une alternative dans la partie 3, avec les BFH. Nous étudions cette architecture, en gardant à l'esprit la faisabilité de la solution. Nous avons choisi un BFH à deux voies, avec un filtre analogique passe-bas et un passe-haut. Puis, nous proposons un algorithme d'optimisation des filtres de synthèse pour atteindre nos objectifs de distorsion et de réjection de repliement. Une identification des filtres analogiques est aussi présentée. Finalement, une réalisation physique prouve le concept et valide les limitations théoriques de cette architecture / This thesis is a partnership between the BL TVFE of NXP Semiconductors and ESIEE. Its goal is to provide a solution to multi-channel reception for cable network. This is linked to the problematic of broadband digitization. In the first part, the state-of-the art of ADCs, parallel architectures (TI and HFB) and sampling methods (bandpass sampling and complex sampling) is recalled. Then we study an architecture called RFFB with a bank of analog filters and a bank of ADCs. We try to reduce the constraints on ADCs, especially the sampling rate with the different sampling. We propose an interesting solution to broadband digitization and compare this solution to a challenging wideband ADC, using the cost function we introduce. This architecture has the major advantage that all the components are feasible, even the ADCs, and it is possible to switch-off subbands to save power. It could be a good solution at the present time but it is not competitive in terms of power consumption and surface. An alternative is proposed in Part 3, where we study Hybrid Filter Banks. It is interesting to study this architecture with realization feasibility in mind. This is why we select a 2-channel HFB with a lowpass filter and a highpass filter as analog filters. Then we propose an efficient optimization algorithm to find the best synthesis filters and reach our targets of distortion and aliasing rejection. An identification of analog filters is also suggested to cope with the issue of sensitivity to analog errors. Finally, a physical realization proves the concept of aliasing rejection and confirms the theoretical issues of this architecture

<div>Target detection, estimation, and discrimination have long been important research issues in the field of radar. Waveform design, analog signal processing, and digital signal processing are some techniques that can improve the detection, estimation, and discrimination ability. In this dissertation, we first address the sidelobe suppression from the waveform design point of view. We synthesize a non-constant modulus waveform for illumination of radar targets by applying a collection of constant modulus (linear frequency modulated (LFM) waveforms with different frequency offsets) waveforms from each transmitting array element in an antenna array, and we show from the ambiguity function that the non-constant modulus waveform has better performance with respect to the larger ambiguity function mainlobe-to-peak-sidelobe ratio than this ratio of a constant modulus (LFM-only) waveform. Furthermore, from the angular resolution point of view, the synthesized non-constant modulus waveform also has better performance than the angular resolution of a constant modulus waveform at the expense of the decrease in the signal energy on targets.</div><div><br></div><div>Secondly, we investigate radar delay-Doppler resolution enhancement from the digital signal processing viewpoint. We introduce the noise-target fringe analysis technique and combine it with the coherent CLEAN algorithm to provide accurate target parameter estimates in terms of delay, Doppler shift and intensity. Furthermore, the accuracy of target parameter estimates can be further improved by applying weighted non-linear least squares estimation.</div><div><br></div><div>Finally, we further aim for the improvement in radar delay-Doppler resolution. Instead of using the matched filter only, we propose a hybrid filter which combines a chirp matched filter and chirp mismatched filters. The hybrid filter output response shows much better performance in delay and Doppler resolution compared to the chirp matched filter output response. Thus, this hybrid filter design has better target identification capability than the original chirp matched filter. Furthermore, from a real implementation perspective, there is no need to significantly increase the hardware and software complexity of the radar, since we only need to mismatch the received waveform to another chirp waveform and perform some additional non-linear processing. Then a chirp radar system with high delay-Doppler resolution and accurate target discrimination ability can be easily achieved.</div>