This work develops novel algorithms for incorporating prior-support information into the field of One-Bit Compressed Sensing. Traditionally, Compressed Sensing is used for acquiring high-dimensional signals from few linear measurements. In applications, it is often the case that we have some knowledge of the structure of our signal(s) beforehand, and thus we would like to leverage it to attain more accurate and efficient recovery. Additionally, the Compressive Sensing framework maintains relevance even when the available measurements are subject to extreme quantization. Indeed, the field of One-Bit Compressive Sensing aims to recover a signal from measurements reduced to only their sign-bit. This work explores avenues for incorporating partial-support information into existing One-Bit Compressive Sensing algorithms. We provide both a rich background to the field of compressed sensing and in particular the one-bit framework, while also developing and testing new algorithms for this setting. Experimental results demonstrate that newly proposed methods of this work yield improved signal recovery even for varying levels of accuracy in the prior information. This work is thus the first to provide recovery mechanisms that efficiently use prior signal information in the one-bit reconstruction setting.

Made available in DSpace on 2016-12-12T17:38:33Z (GMT). No. of bitstreams: 1 Felipe Cubas Schulz.pdf: 4229454 bytes, checksum: cd3b6e0665b2e8aa21c05c4e5922388d (MD5) Previous issue date: 2013-08-30 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Recently, automation systems have been widely investigated. Nowadays, they are present in our lives when shopping, banking, working at home or office. Technology innovations have been increased and embedded into medical and biological equipments, where patients can be better monitored for treatment and diagnosis. These allow precise and ergonomic equipments be designed, especially when using wireless sensor networks. It is developed in this work a biomedical signal acquisition system by suing a wireless sensor network and the Zigbee technology for communication. It was implemented a system for acquiring and processing biomedical data by using commercial sensor modules for wireless communication to a host computer. Also, it was developed a graphical interface in order to manage the sensors of the network and to display the acquired signals to the user. This work has integrated there types of sensors, such as blood oxygenation, heart rate and body temperature. The sensors were chosen due to their easy accessibility and by the fact these type of signals are the most monitored in medicine. Performance tests of sensors network were made to investigate the transmission, reception and data visualization, as well as the communication distance. Also, signal acquisitions were performed in 3 healthy volunteers aged 28, 25 and 65 and the results were compared with the signals acquired by commercial equipments. The results showed that the performance of the blood oxygenation sensor was similar for the three volunteers when compared to the commercial systems. On the other hand, the measured heartbeat by the proposed system showed a greater variation. The body temperature sensor showed reliable readings with a maximum error of approximately 2%. The communication distance of the network was approximately 13 meters in an environment with walls and without the use of routers. It can be concluded that the use of Zigbee sensor network for monitoring bioelectrical signals can be easily implemented and embedded to medical equipments due to its great flexibility when compared to systems which use wired technologies. / A automação de sistemas vem se disseminando muito nos últimos anos, estando presente em nosso dia a dia quando fazemos compras, vamos ao banco ou mesmo estando em nossas casas ou trabalho. Neste contexto vem crescendo o número de oportunidades de se inserir novas tecnologias e automação também na área da medicina, onde o monitoramento de pacientes torna diagnósticos mais fáceis, precisos e ergonômicos, principalmente quando utilizamos redes de transmissão de dados sem fios. Neste trabalho foi desenvolvido um sistema de aquisição de sinais biomédicos sem fio em uma rede de sensores utilizando comunicação Zigbee. Foi implementado uma plataforma de aquisição e processamento de dados biomédicos, utilizando módulos sensores de comunicação sem fio com um computador. Também, um software foi desenvolvido para gerenciar os dispositivos presentes na rede e visualizar os sinais adquiridos ao usuário. Este trabalho integrou sensores de oxigenação do sangue, batimentos cardíacos e temperatura corporal, os quais foram escolhidos por serem considerados sinais vitais de fácil acesso. Testes de desempenho da rede de sensores foram realizados a fim de verificar a transmissão, recepção e visualização dos dados, bem como a distância de comunicação. Também, aquisição de sinais foram realizados em 3 voluntários saudáveis com idades de 28, 25 e 65 anos e os resultados foram comparados com os sinais adquiridos por equipamentos comerciais. Os resultados obtidos mostraram que o sensor de oxigenação do sangue apresentou desempenho similar para os 3 voluntários quando comparados ao sistema comercial. O sensor de batimentos cardíacos apresentou maior variação entre os valores médios pelo sistema proposto. O sensor de temperatura corporal apresentou leituras com um erro sistêmico de aproximadamente 2%. A utilização do protocolo de comunicação Zigbee em uma rede de sensores biomédicos permitiu o monitoramento contínuo de pacientes com maior flexibilidade de uso quando comparado a sistemas convencionais com tecnologias com fios. O alcance da rede chegou a aproximadamente 13 metros em um ambiente com paredes, sem o uso de roteadores. Outros sinais podem ser facilmente adicionados ao sistema e monitorados pela rede de sensores.

Este trabalho descreve o projeto, a construção e a avaliação de um digitalizador de sinais controlado por microprocessador, desenvolvido para ser utilizado em Tomografia por Ressonância Magnética Nuclear, TORM. O digitalizador apresenta dois canais de entrada com digitalização simultânea em 256, 512 ou 1024 palavras por canal e com taxa de amostragem máxima de 22,7 Khz. A resolução é de 12 bits com conversão analógico/digital por aproximação sucessiva. Não há controles manuais o que exige um computador hospedeiro para o ajuste de parâmetros via interface de comunicação paralela destinada para este fim. Opcionalmente pode-se utilizar uma interface serial do tipo RS232C-EIA operando com velocidade máxima de 9600 bauds. O equipamento efetua o processamento local da média acumulativa do sinal, técnica empregada para melhorar a relação sinal/ruído no caso de ruído aleatório. Um circuito dedicado à monitoração permite que se visualize em monitor X-Y tanto o sinal como a sua média. No caso da média, por ela ser acumulativa, há um ajuste automático de escala / This work describes the design, construction and evaluation of a microprocessor controlled digitizer developed to be used in Magnetic Resonance Tomography or Imaging, MRI. The digitizer presents two input channels with simultaneous digitalization in 256, 512 or 1024 words per channel with a sample rate up to 22.7 Khz. A resolution of 12 bits is obtained with successive approximation A/D conversion. There are no manual controls. So a host computer is needed to adjust the parameters through a parallel communication interface available for this purpose. Optionally, a RS232-EIA type serial interface may be used, operating at speeds up to 9600 bauds. Signal average can be processed locally by the equipment. This technique is used to improve the signal to noise ratio in case of random noise. A dedicated circuit permits the visualization of the signal and or its average on an x-y monitor. To monitor cumulative averaged data an automatic scale adjustment is provided

International Telemetering Conference Proceedings / October 23-26, 2000 / Town & Country Hotel and Conference Center, San Diego, California / Range to an orbiting satellite from a ground reference point (ground station) can be determined by measuring the round trip time for a waveform transmitted to the satellite and returned to the ground station (Turnaround Ranging) and more recently by using the Global Positioning System (GPS). This paper first summarizes and compares the two approaches. The paper then describes and analyzes a new turn-around ranging system which uses a flexible ranging waveform that provides spectral compatibility with existing Military, NASA, and Commercial satellite uplink/downlink signals.

A software GPS receiver is a functional GPS receiver in software. It has several advantages compared to its hardware counterparts. For instance, improvements in receiver architecture as well as GPS system structure can be easily adapted to it. Furthermore, interaction between nearby sensors can be coordinated easily. In this thesis, a SGR (software GPS receiver) is presented from a practical point of view. Major components of the SGR are implemented in Matlab environment. Furthermore, some alternative algorithms are implemented. SGR implementation is considered in two main sections namely a signal processing section and a navigation section. Signal processing section is driven by the raw GPS signal samples obtained from a GPS front-end of NordNavTM R-25 instrument. The conventional and the block adjustment of synchronizing signal (BAAS) processing methods are implemented and their performances are compared in terms of their speed and outputs. Signal processing section outputs raw GPS measurements and navigation data bits. Since the output data length is insufficient in our case, navigation section input is fed from AshtechTM GPS receiver for a moving platform and TrimbleTM GPS Receiver for a stationary platform. Satellite position computation, pseudorange corrections, Kalman filter and LSE (least squares estimation) are implemented in the navigation section. Kalman filter and LSE methods are compared in terms of positioning accuracy for a moving as well as a stationary platform. Results are compared with the commercial GPS outputs. This comparison shows that the software navigation section is equivalent to the commercial GPS in terms of positioning accuracy.

We present hereafter the development of the Liebherr Intelligent Hydraulic Cylinder, in which the hydraulic component is used as smart sensing element providing useful information for the system in which the cylinder is operated. The piston position and velocity are the most important signals derived from this new measuring approach. The performance under various load and temperature conditions (measured both on dedicated test facilities and in field in a real machine) will be presented. An integrated control electronics, which is performing the cylinder state processing, additionally allows the synchronized acquisition of external sensors. Providing comprehensive state information, such as temperature and system pressure, advanced control techniques or monitoring functions can be realized with a monolithic device. Further developments, trends and benefits for the system architecture will be briefly analyzed and discussed.

<p dir="ltr">Parkinson’s Disease (PD) is the second most common neurodegenerative disorder with tremor being its primary motor symptom. Although the MS-UPDRS is the current clinical method for evaluating the severity of tremors in PD, it has several drawbacks resulting from the subjective, visual-based examination, and the ordinal scale used to rate the tremors. Since, the MS-UPDRS is agnostic to the etiology of the tremor, age related increase in naturally occurring physiological tremors may confound the precise rating of PD tremors. However, replacing the judgment of the neurologist in determining the holistic progression of PD and treatment protocol is neither feasible nor advisable. This research used lightweight, wearable, non-invasive sensors to detect, analyze, and differentiate changes in wrist kinematics due to physiological and PD tremors. Findings reveal key differences and similarities in composition between these different types of tremors. Dominant frequency analysis using a data-based approach shows interesting parallels with the frequency range found in literature for these tremors. Finally, using features of tremor signal obtained from the sensors, a novel Tremor Severity Score rating scale was created that shows greater sensitivity in differentiating rest and postural tremors as well as medication effects on these tremors in PD patients compared to the MS-UPDRS. This study offers a simple method for objectively evaluating Parkinsonian tremors, identifying kinematic distinctions between rest and postural tremors, analyzing the effect of anti-parkinsonian medication on these tremors, and sensitively scoring tremors. These objective methods could be valuable for early diagnosis and distinguishing between different tremor causes in both clinical and telehealth settings, as well as for investigating the effects of various treatment methods on tremors.</p>

Data acquisition from multiple analog channels is an important function in many embedded devices used in avionics, medical electronics, robotics and space applications. It is desirable to engineer these systems to reduce their size, power consumption, heat dissipation and cost. The goal of this research is to explore designs that exploit a priori knowledge of the input signals in order to achieve these objectives. Sparsity is a commonly observed property in signals that facilitates sub-Nyquist sampling and reconstruction through compressed sensing, thereby reducing the number of A to D conversions. New architectures are proposed for the real-time, compressed acquisition of streaming signals. A. It is demonstrated that by sampling a collection of signals in a multiplexed fashion, it is possible to efficiently utilize all the available sampling cycles of the analogue-to-digital converters (ADCs), facilitating the acquisition of multiple signals using fewer ADCs. The proposed method is modified to accommodate more general signals, for which spectral leakage, due to the occurrence of non-integral number of cycles in the reconstruction window, violates the sparsity assumption. When the objective is to only detect the constituent frequencies in the signals, as against exact reconstruction, it can be achieved surprisingly well even in the presence of severe noise (SNR ~ 5 dB) and considerable undersampling. This has been applied to the detection of the carrier frequency in a noisy FM signal. Information redundancy due to inter-signal correlation gives scope for compressed acquisition of a set of signals that may not be individually sparse. A scheme has been proposed in which the correlation structure in a set of signals is progressively learnt within a small fraction of the duration of acquisition, because of which only a few ADCs are adequate for capturing the signals. Signals from the different channels of EEG possess significant correlation. Employing signals taken from the Physionet database, the correlation structure of nearby EEG electrodes was captured. Subsequent to this training phase, the learnt KLT matrix has been used to reconstruct signals of all the electrodes with reasonably good accuracy from the recordings of a subset of electrodes. Average error is below 10% between the original and reconstructed signals with respect to the power in delta, theta and alpha bands: and below 15% in the beta band. It was also possible to reconstruct all the channels in the 10-10 system of electrode placement with an average error less than 8% using recordings on the sparser 10-20 system. In another design, a set of signals are collectively sampled on a finer sampling grid using ADCs driven by phase-shifted clocks. Thus, each signal is sampled at an effective rate that is a multiple of the ADC sampling rate. So, it is possible to have a less steep transition between the pass band and the stop band, thereby reducing the order of the anti-aliasing filter from 30 to 8. This scheme has been applied to the acquisition of voltages proportional to the deflection of the control surfaces in an aerospace vehicle. The idle sampling cycles of an ADC that performs compressive sub-sampling of a sparse signal, can be used to acquire the residue left after a coarse low-resolution sample is taken in the preceding cycle, like in a pipelined ADC. Using a general purpose, low resolution ADC, a DAC and a summer, one can acquire a sparse signal with double the resolution of the ADC, without having to use a dedicated pipelined ADC. It has also been demonstrated as to how this idea can be applied to achieve a higher dynamic range in the acquisition of fetal electrocardiogram signals. Finally, it is possible to combine more than one of the proposed schemes, to handle acquisition of diverse signals with di_erent kinds of sparsity. The implementation of the proposed schemes in such an integrated design can share common hardware components so as to achieve a compact design.

Robust signal acquisition is an important task in DS-SS receivers. The objective of the acquisition is to coarsely estimate the signal parameters such that the succeeding parameter tracking algorithms can be initialized. In particular, acquisition is needed to coarsely synchronize the receiver to the timing and frequency of the received signal. For this purpose mainly data aided and feedforward algorithms are applied. Using the maximum likelihood (ML) criterion, an estimator for the joint estimation of receive timing and frequency offset can be derived which determines the maximum of the Likelihood function over the whole parameter uncertainty region. Due to its high complexity the ML synchronizer is difficult to implement for practical applications. Hence, complexity reduced algorithms need to be derived. This thesis gives a systematic survey of acquisition algorithms and of performance analysis methods for analyzing such algorithms under mobile radio propagation conditions. The exploitation of multiple observations is investigated in order to improve the acquisition performance in terms of false alarm rate and acquisition time. In particular, optimal and suboptimal combining schemes for a fixed observation interval as well as sequential utilization of successive observations resulting in a variable observation length are analyzed. Another possibility to make the signal acquisition more efficient in terms of the acquisition time is to use multi stage acquisition algorithms. One class of those algorithms are the well known multiple dwell algorithms. A different approach is to design acquisition procedures in which the information about the unknown parameters is distributed among several stages such that each stage has to cope with a smaller uncertainty region in comparison to the overall parameter uncertainty. Analysis of multi stage algorithms followed by an extensive discussion of the 3GPP FDD downlink acquisition procedure as an example of a multi stage procedure with distributed information conclude the work. / Die zuverlässige Signalakquisition, die auch als Grobsynchronisation bezeichnet wird, stellt eine wichtige Aufgabe in DS-SS-Systemen dar. Das Ziel hierbei ist es, Schätzwerte fur die Übertragungsparameter derart zu bestimmen, dass die der Grobsynchronisation nachfolgende Feinsynchronisation initialisiert werden kann, d. h. dass die bestimmten Schätzwerte innerhalb des Fangbereiches der Feinsynchronisationsalgorithmen liegen. Insbesondere ist es für die Bestimmung von Synchronisationszeitpunkt und Frequenzversatz sinnvoll, eine Grobsynchronisation durchzuführen. Im Interesse einer begrenzten Komplexität sowie einer möglichst schnellen Akquisition finden vor allem datengestützte und vorwärtsverarbeitende Algorithmen Anwendung. Ausgehend vom Maximum-Likelihood-Kriterium (ML-Kriterium) können geeignete Schätzer für die gemeinsame Bestimmung von Synchronisationszeitpunkt und Frequenzversatz abgeleitet werden. Dabei ist das Maximum der Likelihood-Funktion innerhalb der Parameterunsicherheitsregion zu bestimmen. Aufgrund seiner hohen Komplexität ist der ML-Schatzer fur die Akquisition wenig geeignet; vielmehr müssen aufwandsgünstige Algorithmen mit ausreichender Leistungsfähigkeit gefunden werden. In dieser Arbeit werden verschiedene Algorithmen zur Parameterakquisition systematisierend gegenübergestellt. Weiterführend sind Verfahren zur Verbesserung des Akquisitionsverhaltens bezüglich Fehlalarm-Wahrscheinlichkeit und Akquisitionszeit unter Ausnutzung mehrfacher Beobachtung Gegenstand der Betrachtungen. Insbesondere optimale und suboptimale Verfahren mit fester Beobachtungsdauer sowie die sequentielle Auswertung aufeinander folgender Beobachtungen, bei der sich die Beobachtungsdauer nach der erreichten Entscheidungssicherheit bestimmt, werden analysiert. Als eine weitere Möglichkeit, die Signalakquisition in Bezug auf die Akquisitionszeit effizienter zu gestalten, werden mehrstufige Akquisitionsverfahren diskutiert. Es werden zum einen die häufig genutzten Mehrfach-Dwell-Algorithmen sowie mehrstufige Algorithmen mit verteilter Information betrachtet. Bei Letzteren Algorithmen wird jeder Akquisitionsstufe ein Teil der zur Synchronisation benötigten Information zugeordnet, wodurch sich die Parameter-Unsicherheit für jede einzelne Stufe verringert. Ziel hierbei ist es, durch Erhöhung der Entscheidungssicherheit der einzelnen Stufen die mittlere Akquisitionszeit zu reduzieren. Die Diskussion und die Analyse von mehrstufigen Akquisitionsverfahren bilden den Abschluss der Arbeit, wobei besonders auf die 3GPP-FDD Downlink-Akquisition als ein Beispiel fur mehrstufige Verfahren mit verteilter Information eingegangen wird.

Die Charakterisierung von Dispersionen hat das Ziel, die Zusammensetzung und den Zustand von partikelhaltigen Stoffgemischen zu erfassen. Vor allem der Zustand der dispersen Phase (Partikel), der wiederum von der Größe und der Konzentration der Partikel bestimmt wird, ist in diesem Zusammenhang von besonderer Bedeutung. Neben optischen Verfahren, wie der Laserbeugung oder der Lichtstreuung, ist die Anwendung von akustischen Methoden vor allem dann sinnvoll, wenn die zu untersuchenden dispersen Stoffgemische opak und optische Methoden nur noch eingeschränkt (nach Verdünnung) anwendbar sind. Derartige Dispersionen weisen oftmals eine hohe Partikelkonzentration auf. Die Erfassung und Auswertung von Ultraschallechosignalen aus konzentrierten Dispersionen stellt einen neuartigen Ansatz innerhalb der akustischen Partikelmesstechnik dar. Im Rahmen der vorliegenden Arbeit wurden theoretische und experimentelle Untersuchungen zum Ultraschallrückstreuverhalten von konzentrierten Dispersionen im unteren Megahertzbereich durchgeführt. Die messtechnische Erfassung der von der Dispersion reflektierten Schallanteile stellte eine besondere Herausforderung dar. Vor allem bei Partikeln, die klein gegenüber der Wellenlänge des Schalls sind oder einen geringen akustischen Kontrast gegenüber der kontinuierlichen Phase aufweisen, ist ein entsprechend schwaches Echosignal zu erwarten. Im Ergebnis der durchgeführten Untersuchungen zeigt sich eine hohe Sensitivität des akustischen Rückstreuverhaltens gegenüber der Zusammensatzung der Dispersion. Vor allem in konzentrierten Dispersionen kann die Messung direkt, d. h. ohne vorherige Verdünnung durchgeführt werden. Dieser Umstand prädestiniert das entwickelte Messverfahren für den Einsatz innerhalb der prozessnahen Charakterisierung von Partikelsystemen, beispielsweise bei Nasszerkleinerungs- oder Kristallisationsprozessen. Bei derartigen Prozessen ist eine Probenahme und Probenaufbereitung nicht oder nur eingeschränkt möglich.