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Andrikogiannopoulos, Nikolas I. "RF phase modulation of optical signals and optical/electrical signal processing." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/42930.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Includes bibliographical references (p. 125-127).<br>Analog RF phase modulation of optical signals has been a topic of interest for many years, mainly focusing on Intensity Modulation Direct Detection (IMDD). The virtues of coherent detection combined with the advantages of Frequency Modulation, however, have not been explored thoroughly. By employing Frequency Modulation Coherent Detection (FMCD), the wide optical transmission bandwidth of optical fiber can be traded for higher signal-to-noise performance. In this thesis, we derive the FM gain over AM modulation -- the maximum achievable signal-to-noise ratio (by spreading the signal's spectrum) for specific carrier-to-noise ratio. We then employ FMCD for a scheme of remote antennas for which we use optical components and subsystem to perform signal processing such as nulling of interfering signals. The performance of optical processing on different modulation schemes are compared, and some important conclusions are reported relating to the use of conventional FMCD, FMCD with optical discriminator (FMCD O-D), and IMDD. Specifically, the superiority of conventional FMCD is shown; and, on the other hand, the inferiority of FMCD O-D is shown (same performance as IMDD) because of the use of an O-D. Finally, the remote antenna scheme is generalized for N antennas and N users.<br>by Nikolas I. Andrikogiannopoulos.<br>S.M.
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Ghaderi, Foad. "Signal processing techniques for extracting signals with periodic structure : applications to biomedical signals." Thesis, Cardiff University, 2010. http://orca.cf.ac.uk/55183/.
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In this dissertation some advanced methods for extracting sources from single and multichannel data are developed and utilized in biomedical applications. It is assumed that the sources of interest have periodic structure and therefore, the periodicity is exploited in various forms. The proposed methods can even be used for the cases where the signals have hidden periodicities, i.e., the periodic behaviour is not detectable from their time representation or even Fourier transform of the signal. For the case of single channel recordings a method based on singular spectrum anal ysis (SSA) of the signal is proposed. The proposed method is utilized in localizing heart sounds in respiratory signals, which is an essential pre-processing step in most of the heart sound cancellation methods. Artificially mixed and real respiratory signals are used for evaluating the method. It is shown that the performance of the proposed method is superior to those of the other methods in terms of false detection. More over, the execution time is significantly lower than that of the method ranked second in performance. For multichannel data, the problem is tackled using two approaches. First, it is assumed that the sources are periodic and the statistical characteristics of periodic sources are exploited in developing a method to effectively choose the appropriate delays in which the diagonalization takes place. In the second approach it is assumed that the sources of interest are cyclostationary. Necessary and sufficient conditions for extractability of the sources are mathematically proved and the extraction algorithms are proposed. Ballistocardiogram (BCG) artifact is considered as the sum of a number of independent cyclostationary components having the same cycle frequency. The proposed method, called cyclostationary source extraction (CSE), is able to extract these components without much destructive effect on the background electroencephalogram (EEG)
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Gartheeban, Ganeshapillai. "Methods to improve the signal quality of corrupted multi-parameter physiological signals." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/65969.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student submitted PDF version of thesis.<br>Includes bibliographical references (p. 121-125).<br>A modern Intensive Care Unit (ICU) has automated analysis systems that depend on continuous uninterrupted real-time monitoring of physiological signals such as Electrocardiogram (ECG), Arterial Blood Pressure (ABP), and the Photo Plethysmogram (PPG). Unfortunately, these signals are often corrupted by noise, artifacts, and missing data, which can result in a high incidence of false alarms. We present a novel approach to improve the Signal Quality of a multi-parameter physiological signal by identifying the corrupted regions in the signal, and reconstructing them using the information available in correlated signals. The method is specifically designed to preserve the clinically most signicant aspects of the signals. We use template matching to jointly segment the multi-parameter signal, morphological dissimilarity to estimate the quality of the signal segment, similarity search to nd the closest match from a database of templates, and time-warping to reconstruct the corrupted segment using the matching template. Experiments carried out on the MIT-BIH Arrhythmia Database, a multi-parameter ECG database with many clinically signicant arrhythmias, demonstrate the effectiveness of the method. Our method improved the classification accuracy of the beat type by more than 700% on the signal corrupted with white Gaussian noise, and increased the similarity to the original signal, as measured by the normalized residual distance, by more than 250%. When the method was applied to the multi-parameter physiological signal data from Cinc Challenge 2010 database at Physionet.org, our method improved the classification accuracy of beat type by more than 33 times on a signal corrupted with white Gaussian noise, and increased the similarity to the original signal by more than 280%.<br>by Gartheeban Ganeshapillai.<br>S.M.
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Nguyen, Thien-Minh. "Contribution to the analysis and understanting of electrical-grid signals with signal processing and machine learning techniques." Thesis, Mulhouse, 2017. http://www.theses.fr/2017MULH9234/document.
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Ce travail de thèse propose des approches d’identification et de reconnaissance des harmoniques de courant qui sont basées sur des stratégies d’apprentissage automatique. Les approches proposées s’appliquent directement dans les dispositifs d’amélioration de la qualité de l’énergie électrique.Des structures neuronales complètes, dotées de capacités d’apprentissage automatique, ont été développées pour identifier les composantes harmoniques d’un signal sinusoïdal au sens large et plus spécifiquement d’un courant alternatif perturbé par des charges non linéaires. L’identification des harmoniques a été réalisée avec des réseaux de neurones de type Multi–Layer Perceptron (MLP). Plusieurs schémas d’identification ont été développés, ils sont basés sur un réseau MLP composé de neurones linéaire ou sur plusieurs réseaux MLP avec des apprentissages spécifiques. Les harmoniques d’un signal perturbé sont identifiées avec leur amplitude et leur phase, elles peuvent servir à générer des courants de compensation pour améliorer la forme du courant électrique. D’autres approches neuronales a été développées pour reconnaître les charges. Elles consistent en des réseaux MLP ou SVM (Support Vector Machine) et fonctionnent en tant que classificateurs. Leur apprentissage permet à partir des harmoniques de courant de reconnaître le type de charge non linéaire qui génère des perturbations dans le réseau électrique. Toutes les approches d’identification et de reconnaissance des harmoniques ont été validées par des tests de simulation à l’aide des données expérimentales. Des comparaisons avec d’autres méthodes ont démontré des performances supérieures et une meilleure robustesse<br>This thesis proposes identifying approaches and recognition of current harmonics that are based on machine learning strategies. The approaches are applied directly in the quality improvement devices of electric energy and in energy management solutions. Complete neural structures, equipped with automatic learning capabilities have been developed to identify the harmonic components of a sinusoidal signal at large and more specifically an AC disturbed by non–linear loads. The harmonic identification is performed with multilayer perceptron neural networks (MLP). Several identification schemes have been developed. They are based on a MLP neural network composed of linear or multiple MLP networks with specific learning. Harmonics of a disturbed signal are identified with their amplitude and phases. They can be used to generate compensation currents fed back into the network to improve the waveform of the electric current. Neural approaches were developed to distinguish and to recognize the types of harmonics and is nonlinear load types that are at the origin. They consist of MLP or SVM (Support Vector Machine) acting as classifier that learns the harmonic profile of several types of predetermined signals and representative of non–linear loads. They entry are the parameters of current harmonics of the current wave. Learning can recognize the type of nonlinear load that generates disturbances in the power network. All harmonics identification and recognition approaches have been validated by simulation tests or using experimental data. The comparisons with other methods have demonstrated superior characteristics in terms of performance and robustness
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Thomas, Gregoire R. "Agonist : induced electrical signals in the intact lens." Thesis, University of East Anglia, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.338296.
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Hassana, Ramesh Rakesh Kashyap. "Transform Domain Acquisition of Spread Spectrum Signals in a Low Signal to Noise Ratio Environment." Ohio University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1289579500.
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Kershaw, Robert Andrew. "Retrieved voluntary electromyogram signals for functional electrical stimulation control." Thesis, University of Bristol, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295098.
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Bortnik, Bartosz Jan. "Photonic generation, transmission, and detection of high-speed electrical signals." Diss., Restricted to subscribing institutions, 2007. http://proquest.umi.com/pqdweb?did=1459913961&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.
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Masmoudi, Mohamed Lamine. "Détection d'un défaut localisé dans un multiplicateur d'éolienne : approche par analyse des grandeurs électromécaniques." Thesis, La Rochelle, 2015. http://www.theses.fr/2015LAROS001.
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Le travail présenté dans ce mémoire a été effectué dans le cadre du projet FEDER ”Maintenance prédictive des éoliennes et maîtrise des impacts environnementaux”. Un des objectifs du projet a été de développer, dans le Poitou-Charentes, des compétences dans le domaine de l’éolien en lien avec les activités des laboratoires LIAS et LaSIE. Pour le LIAS, il a été décidé de lancer une nouvelle activité de recherche sur le diagnostic de défauts mécaniques. Le cadre du projet concernant l’éolien, les défauts localisés dans les multiplicateurs ont été privilégiés. Par ailleurs, nous avons restreint l’étude au régime stationnaire afin de simplifier l’apprentissage des différents phénomènes mis en jeu et des techniques de traitement du signal utilisées. Dans une première partie, nous avons étudié les signatures de défaut sur les signaux vibratoires. Cette phase a été facilitée par l’utilisation des données expérimentales mise à disposition par le Bearing Data Center de la Case Western Reserve - University de Cleveland. Parmi les méthodes de traitement de signal utilisées, nous avons opté pour l’analyse d’enveloppe mise en oeuvre dans les techniques de type Time Synchronous Analysis (TSA). A cette occasion, nous avons défini une procédure complète de détection de défaut que nous avons conservée tout au long de cette étude en appliquant une technique d’identification de type PNL qui nous a permis d’obtenir des résultats comparables à des méthodes haute résolution de type ESPRIT. Par la suite, nous nous sommes recentrés sur l’application éolienne en réalisant un banc d’essai original permettant d’émuler un défaut au niveau de l’accouplement de deux machines électriques. L’idée principale a été de recenser l’ensemble des signaux exploitables dans le cadre de la détection du défaut émulé et de fournir une classification entre les courants électriques, le couple mécanique et la vitesse des machines. Par ailleurs, un comparatif entre signaux mesurés et signaux estimés a été présenté. Il en ressort qu’il est possible d’obtenir un signal observé plus riche que la mesure directe en terme de composantes spectrales liées au défaut. Cette amélioration est rendue possible par une synthèse adéquate des gains d’observation qui a été obtenue après linéarisation de l’observateur étudié. En marge de l’application éolienne, le cas d’un moteur commandé vectoriellement a été abordé. L’idée a été d’exploiter les performances de la boucle de vitesse afin d’amplifier les composantes recherchées dans les courants électriques. L’ensemble de ces pistes de recherches a été testé en simulation et expérimentalement<br>The work presented in this thesis was carried out under the FEDER project ”Maintenance prédictive des éoliennes et maîtrise des impacts environnementaux”. One of the project objectives was to develop, in Poitou-Charentes, expertise in the field of wind power in connection with the activities of LIAS and LaSIE laboratories. For LIAS, it was decided to launch a new research activity on the diagnosis of mechanical faults. The localized defects in gearbox were privileged. Furthermore, we restricted the study to the stationary system to simplify the learning of different phenomena involved and signal processing techniques. In the first part, we studied the fault signatures on the vibration signals. This phase was facilitated by the use of experimental data available from the Bearing Data Center of the Case Western Reserve - Cleveland University. Among the signal processing methods, we opted for envelope analysis implemented in the Synchronous Time Averaging (TSA). On this occasion, we defined a comprehensive fault detection procedure that we have maintained throughout this study by applying a NLP identification technique where we obtained similar results compared to high-resolution methods as ESPRIT. There after, we refocused on wind power applications by making an original test bench capable of emulating a fault in the coupling of two electrical machines. The main idea was to identify all usable signals in the context of emulated fault detection and to provide a classification between electric currents, mechanical torque and speed of the machines. Moreover, a comparison between measured signals and estimated ones was discussed. It shows that it is possible to get an observed signal richer than direct signal measurement in terms of spectral components related to the defect. This improvement is made possible by an appropriate synthesis of gains observer which was obtained after linearization of the studied observer. In the margin of wind application, the case of a motor controlled by vector was also discussed. The idea was to exploit the speed loop performance to amplify the fault components in electrical currents. All these researches have been tested in simulation and experimentally
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Naidoo, Thoneshan. "Signal and image processing for electrical resistance tomography." Master's thesis, University of Cape Town, 2002. http://hdl.handle.net/11427/5140.
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Bibliography: leaves 139-150.<br>Electrical Resistance Tomography (ERT) is in essence an imaging technique.In ERT current is injected into and removed from a vessel via paired electrodes. The resulting voltage measurements are captured between the remaining electrode pairs. The principle behind ERT is to map these boundary voltages into a conductivity distribution that represents the domain of the vessel. The author has coded a versatile reconstruction algorithm based on the Newton-Raphson algorithm. The knowledge gained by implementing the algorithm is documented in this thesis. The literature covers the basic aspects of two-dimensional and three-dimensional ERT. It is hoped that this thesis will create a greater interest in ERT at the University of Cape Town (UCT) and also act as a building block for further developments. The thesis starts by presenting the basic concepts of ERT such as the underlying equations, the various boundary measurement strategies and a global perspective of ERT. The nature of this thesis is on software reconstruction and in so doing information on the incorporation of the Finite Element Method in ERT is provided. The thesis goes on to provide information about the reconstruction algorithms, which incorporate regularization. A novel aspect of this thesis involves the calibration and pre-processing of boundary voltages. These concepts were conceptualised and developed during formal communications with Dr. Wilkinson (2002) and Randal (2002). The calibration schemes try to eliminate the potential errors that can arise inthe captured data thus allowing for a clearer image to be reconstructed, Electrical Resistance Tomography. This thesis further develops the idea of parallelizing the Newton-Raphson algorithm to increase the speed of the algorithm. Various schemes on how this parallelization is achievable are put forward.
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Talebinejad, Mehran. "Fractal analysis of myoelectric signals." Thesis, University of Ottawa (Canada), 2006. http://hdl.handle.net/10393/27184.
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In this thesis, we study fractal behavior of myoelectric signals (MESs). Mathematics and definitions behind fractal behavior is presented. Different methods of estimating the fractal dimension are discussed, including time domain-based methods (i.e. Katz method, Box-Counting method) and spectrum based methods (i.e. Power Spectrum Slope Method (PSSM) and General Power Spectrum Method (GPSM)). The GPSM is introduced in context of MESs for the first time. Using simulated MESs effects of its parameters (i.e. number of active motor units (MUs), firing rate and depth of active MUs) on estimated fractal dimension (eFD) and estimated fractal indicators (eFI) are analyzed. Spectrum based methods demonstrate characteristics that suggest superiority in discerning force effects (i.e. number of active MUs and firing rate) and geometric effects (i.e. depth of active MUs). Fractal behavior of MESs during Isometric Constant Force Contractions (ICFC) at different force and joint angles are analyzed. Results of the spectrum based methods suggest that they could possibly be used to estimate the joint angle independent of force. Fractal behavior of MESs during Isometric Voluntary Contractions (IVC) at different force and joint angles are analyzed as well. Results, although highly variable, remain consistent with the simulated results.
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Zhao, Mingmin S. M. Massachusetts Institute of Technology. "Emotion recognition using wireless signals." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112055.
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Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 47-52).<br>This thesis demonstrates a new technology that can infer a person's emotions from RF signals reflected off his body. EQ-Radio transmits an RF signal and analyzes its reflections off a person's body to recognize his emotional state (happy, sad, etc.). The key enabler underlying EQ-Radio is a new algorithm for extracting the individual heartbeats from the wireless signal at an accuracy comparable to on-body ECG monitors. The resulting beats are then used to compute emotion-dependent features which feed a machine-learning emotion classifier. We describe the design and implementation of EQ-Radio, and demonstrate through a user study that its emotion recognition accuracy is on par with state-of-the-art emotion recognition systems that require a person to be hooked to an ECG monitor.<br>by Mingmin Zhao.<br>S.M.
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Lahlou, Tarek A. (Tarek Aziz). "Parameter recovery for transient signals." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/82406.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 115-118).<br>Transient signals naturally arise in numerous disciplines for which the decay rates and amplitudes carry some informational significance. Even when the decay rates are known, solving for the amplitudes results in an ill-conditioned formulation. Transient signals in the presence of noise are further complicated as the signal-to-noise ratio asymptotically decreases in time. In this thesis the Discrete-Time Transient Transform and the Discrete Transient Transform are defined in order to represent a general signal using a linear combination of decaying exponential signals. A common approach to computing a change of basis is to make use of the dual basis. Two algorithms are proposed for generating a dual basis: the first algorithm is specific to a general exponential basis, e.g., real exponential or harmonically related complex exponential bases are special cases of the general exponential basis, while the second algorithm is usable for any general basis. Several properties of a transient domain representation are discussed. Algorithms for computing numerically stable approximate transient spectra are additionally proposed. The inherent infinite bandwidth of a continuous-time transient signal motivates in part the development of a framework for recovering the decay rates and amplitudes of a discrete-time lowpass filtered transient signal. This framework takes advantage of existing parameter modeling, identification, and recovery techniques to determine the decay rates while an alternating projection method utilizing the Discrete Transient Transform determines the amplitudes.<br>by Tarek A. Lahlou.<br>S.M.
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Hall, Timothy Douglas 1970. "Radiolocation using AM broadcast signals." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/16898.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.<br>Includes bibliographical references (p. 293-294).<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>(cont.) Previous attempts at signal-of-opportunity navigation using carrier phase sidestepped the ambiguity problem by requiring that the initial position of the rover be known and that phase variations be tracked without interruption. I designed and implemented an ambiguity-function method that enables the phase ambiguity to be resolved instantaneously without position initialization or signal-tracking continuity. I encountered several impediments to AM-broadcast-based radiolocation that, if not dealt with appropriately, reduce positioning accuracy, reduce ambiguity-resolution robustness, or both. AM transmitter position uncertainty directly causes receiver position-determination uncertainty. Since the error in published antenna positions sometimes exceeds 100 meters, I conducted sub-meter-accuracy geodetic surveys of 29 Boston-area AM-broadcast antennas. The directional radiation patterns of the array antennas of many AM broadcast radio stations have phases that vary with azimuth angle. I developed and implemented a model for the phase of a directional antenna that nearly eliminated theerrors caused by this effect. AM broadcast signals travel primarily as groundwaves, which propagate with phase velocities that depend on the electrical properties of the ground. Using simulations and empirical data, I designed and implemented a model for groundwave propagation that greatly reduced the errors caused by this effect over a broad geographic area ...<br>by Timothy Douglas Hall.<br>Ph.D.
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Anderson, Mark David. "Pitch determination of speech signals." Thesis, Massachusetts Institute of Technology, 1986. http://hdl.handle.net/1721.1/14999.
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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1986.<br>MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING<br>Bibliography: leaves 138-147.<br>by Mark David Anderson.<br>M.S.
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Kusuma, Julius. "Economical sampling of parametric signals." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/38225.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.<br>Includes bibliographical references (p. 107-115).<br>This thesis proposes architectures and algorithms for digital acquisition of parametric signals. It furthermore provides bounds for the performance of these systems in the presence of noise. Our simple acquisition circuitry and low sampling rate enable accurate parameter estimation to be achieved economically. In present practice, sampling and estimation are not integrated: the sampling device does not take advantage of the parametric model, and the estimation assumes that noise in the data is signal-independent additive white Gaussian noise. We focus on estimating the timing information in signals that are linear combinations of scales and shifts of a known pulse. This signal model is well-known in a variety of disciplines such as ultra-wideband signaling, neurobiology, etc. The signal is completely determined by the amplitudes and shifts of the summands. The delays determine a subspace that contains the signals, so estimating the shifts is equivalent to subspace estimation. By contrast, conventional sampling theory yields a least-squares approximation to a signal from a fixed shift-invariant subspace of possible reconstructions. Conventional acquisition takes samples at a rate higher than twice the signal bandwidth.<br>(cont.) Although this may be feasible, there is a trade-off between power, accuracy, and speed. Under the signal model of interest, when the pulses are very narrow, the number of parameters per unit time-the rate of innovation-is much lower than the Fourier bandwidth. There is thus potential for much lower sampling rate so long as nonlinear reconstruction algorithms are used. We present a new sampling scheme that takes simultaneous samples at the outputs of multiple channels. This new scheme can be implemented with simple circuitry and has a successive approximation property that can be used to detect undermodeling. In many regimes our algorithms provide better timing accuracy and resolution than conventional systems. Our new analytical and algorithmic techniques are applied to previously proposed systems, and it is shown that all the systems considered have super-resolution properties. Finally, we consider the same parameter estimation problem when the sampling instances are perturbed by signal-independent timing noise. We give an iterative algorithm that achieves accurate timing estimation by exploiting knowledge of the pulse shape.<br>by Julius Kusuma.<br>Ph.D.
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Sarda, Srikant 1977. "Neural networks and neurophysiological signals." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/9806.
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Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.<br>Includes bibliographical references (p. 45).<br>The purpose of this thesis project is to develop, implement, and validate a neural network which will classify compound muscle action potentials (CMAPs). The two classes of signals are "viable" and "non-viable." This classification system will be used as part of a quality assurance mechanism on the NC-stat nerve conduction monitoring system. The results show that standard backpropagation neural networks provide exceptional classification results on novel waveforms. Also, principal components analysis is a powerful preprocessing technique which allows for a significant reduction in processing efficiency, while maintaining performance standards. This system is implementable as a real-time quality control process for the NC-stat.<br>by Srikant Sarda.<br>S.B.and M.Eng.
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Najafzadeh-Azghandi, Hossein. "Perceptual coding of narrowband audio signals." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0033/NQ64628.pdf.
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Edmonds, Christopher Albin. "Adaptive segmenting of non-stationary signals." FIU Digital Commons, 1998. http://digitalcommons.fiu.edu/etd/3116.
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Many data compression techniques rely on the low entropy and/or the large degree of autocorrelation exhibited by stationary signals. In non-stationary signals, however, these characteristics are not constant, resulting in reduced data compression efficiency. An adaptive scheme is developed that divides non-stationary signals into smaller locally stationary segments, thereby improving overall efficiency. Two principal issues arise in implementing this procedure. The first is practical; an exhaustive search of all possible segmentations is in general computationally prohibitive. The concept of dynamic programming is applied to reduce the expense of such a search. The second involves choosing a cost function that is appropriate for a particular compression method. Two cost functions are employed here, one based on entropy and the other on correlation. It is shown that by using an appropriate cost function, an adaptively segmented signal offers better data compression efficiency than an unsegmented or arbitrarily segmented signal.
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Sellergren, Albin, Tobias Andersson, and Jonathan Toft. "Signal processing through electroencephalography : Independent project in electrical engineering." Thesis, Uppsala universitet, Elektricitetslära, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-298771.
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This report is about a project where electroencephalography (EEG) wasused to control a two player game. The signals from the EEG-electrodeswere amplified, filtered and processed. Then the signals from the playerswere compared and an algorithm decided what would happen in the gamedepending on which signal was largest. The controls and the gaming mechanismworked as intended, however it was not possible to gather a signal fromthe brain with the method used in this project. So ultimately the goal wasnot reached.<br>electroencephalography, EEG
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Riordan, Margaret. "Adaptive equalization for burst signals in dispersive channels." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Dec%5FRiordan.pdf.
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Thesis (M.S. in Engineering Science (Electrical Engineering))--Naval Postgraduate School, December 2005.<br>Thesis Advisor(s): Charles Therrien. Includes bibliographical references (p.59). Also available online.
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Roussel, Benjamin. "Autopsy of a quantum electrical current." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE1285/document.
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Les expériences de physique quantique ont atteint un niveau de contrôle permettant de préparer avec précision l'état quantique de nombreux systèmes physiques. Cela a mené à la naissance de l'optique quantique électronique, un sujet émergent qui vise à préparer, manipuler et caractériser l'état de courants électriques contenant quelques excitations électroniques se propageant dans un conducteur quantique ballistique. Ceci est un défi conséquent qui se heurte à la difficulté de caractériser un état quantique à N corps.Le sujet de cette thèse sera le développement de méthodes de traitement du signal quantique permettant d'accéder à une connaissance partielle d'un tel état pour des courants électriques quantiques. Une première méthode consiste à les analyser à nombre d'excitations fixé au travers des cohérences électroniques. Pour cela, nous élaborons une analyse de la cohérence à un électron en termes d'atomes de signaux électroniques. En combinant cela au protocole de tomographie par interférometrie HOM, nous présentons la première autopsie, fonction d'onde par fonction d'onde, d'un courant électrique quantique.Une autre approche consiste à examiner des indicateurs sondant directement l'état à N corps. Nous étudions le rayonnement émis par un conducteur quantique ainsi que la décohérence électronique d'une excitation à un électron. Ensuite nous analysons la distribution de probabilité de la chaleur dissipée par un système quantique mésoscopique. Dans ce cadre, nous développons une théorie de l'effet Joule en régime quantique et à explorons comment celle-ci pourrait permettre de sonder l'état à N corps<br>Quantum physics experiments have reached a level of precision and control that allows quantum state engineering for many systems. This has led to the birth of electron quantum optics, an emerging field which aims at generating, manipulating and characterizing quantum electrical currents built from few-electron excitations propagating within ballistic quantum conductors. This is challenging since it is generically impossible in practice to fully characterize the many-body state of a beam containing indistinguishable electrons. The thesis presents new quantum signal processing approaches for accessing, at least partially, to the quantum many-body state of quantum electrical currents.A first approach is to access such a state at few-particle levels through electronic coherences. We will thus present a new representation of single-electron coherence in terms of electronic "atoms of signal". Combining this signal processing algorithm to HOM tomography enables us to present the first autopsy, wavefunction by wavefunction, of an experimental electrical quantum current. Another method is to look for indicators giving information directly at the many-body level. We will investigate the radiation emitted by a quantum conductor and address the problem of decoherence of a general single-electron excitation. Finally, we will look at the heat deposited by a mesoscopic quantum system, leading to a quantum version of Joule heating and discuss how it gives an insight on the many-body state of the electron fluid
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Hau, David Tak-Wai. "Learning qualitative models from physiological signals." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/34075.
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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.<br>Includes bibliographical references (leaves 165-169).<br>by David Tak-Wai Hau.<br>M.S.
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Sidor, Szymon. "Reinforcement learning with natural language signals." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/103745.
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Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 79-83).<br>In this thesis we introduce a technique that allows one to use Natural Language as part of the state in Reinforcement Learning. We show that it is capable of solving Natural Language problems, similar to Sequence-to-Sequence models, but using multistage reasoning. We use Long Short-Term Memory Networks to parse the Natural Language input, whose final hidden state is used to compute action scores for the Deep Q-learning algorithm. First part of the thesis introduces the necessary theoretical background, including Deep Learning approach to Natural Language Processing, Recurrent Neural Networks and Sequence-to-Sequence modeling. We consider two case studies: translation and dialogue. In addition, we provide an overview of the existing techniques for the Reinforcement Learning problems, with focus on Deep Q-learning algorithm. In the second part of the thesis we present the multi-stage reasoning approach, and demonstrate it on solving the sentence unshuffling problem. It achieves accuracy 5% better than a Sequence-to-Sequence model, while requiring 3 times less examples to converge. Furthermore, we show that our approach is flexible and can be used with multi-modal inputs - Natural Language and agent's sensory data. We propose a system capable of understanding and executing Natural Language commands. It can be used for many different tasks with minimal engineering effort - the only required components being the reward function and example commands. We demonstrate its performance using an experiment in which an agent is required to learn to complete four types of manipulation tasks. The approach achieves nearly perfect performance on two of them and good performance in the two others.<br>by Szymon Sidor.<br>S.M.
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Shavit, Yonadav Goldwasser. "Learning environment simulators from sparse signals." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113442.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 83-85).<br>To allow planning in novel environments that have not been mapped out by hand, we need ways of learning environment models. While conventional work has focused on video prediction as a means for environment learning, this work instead seeks to learn from much sparser signals, like the agent's reward. In Chapter 1, we establish a taxonomy of environments and the attributes that make them easier or harder to model through learning. In Chapter 2, we review prior work in the field of environment learning. In Chapter 3, we propose a model-learning architecture based purely on reward prediction, and analyze its performance on illustrative problems. Finally, in Chapter 4, we propose and evaluate a model-learning architecture that uses both reward and sparse "features" extracted from the environment.<br>by Yonadav Goldwasser Shavit.<br>M. Eng.
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Pai, Ruby J. "Nonadaptive lossy encoding of sparse signals." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/41623.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.<br>Includes bibliographical references (p. 67-68).<br>At high rate, a sparse signal is optimally encoded through an adaptive strategy that finds and encodes the signal's representation in the sparsity-inducing basis. This thesis examines how much the distortion rate (D(R)) performance of a nonadaptive encoder, one that is not allowed to explicitly specify the sparsity pattern, can approach that of an adaptive encoder. Two methods are studied: first, optimizing the number of nonadaptive measurements that must be encoded and second, using a binned quantization strategy. Both methods are applicable to a setting in which the decoder knows the sparsity basis and the sparsity level. Through small problem size simulations, it is shown that a considerable performance gain can be achieved and that the number of measurements controls a tradeoff between decoding complexity and achievable D(R).<br>by Ruby J. Pai.<br>M.Eng.
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Khodam, Hazrati Mehrnaz [Verfasser]. "On human-machine interfaces based on electrical brain signals / Mehrnaz Khodam Hazrati." Lübeck : Zentrale Hochschulbibliothek Lübeck, 2014. http://d-nb.info/1054365644/34.
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Kakarna, Tejaswi. "A 018μm Cmos Transmitter for Ecg Signals". Thesis, University of North Texas, 2013. https://digital.library.unt.edu/ark:/67531/metadc407805/.
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Electrocardiography (ECG) signal transmitter is the device used to transmit the electrical signals of the heart to the remote machine. These electrical signals are ECG signals caused due to electrical activities in the heart. ECG signals have very low amplitude and frequency; hence amplification of the signals is needed to strengthen the signal. Conversion of the amplified signal into digital information and transmitting that information without losing any data is the key. This information is further used in monitoring the heart.
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Li, Xiang. "PHYSICAL LAYER WATERMARKING OF DIRECT SEQUENCE SPREAD SPECTRUM SIGNALS." Cleveland State University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=csu1368527408.
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Wahlqvist, Emanuel. "Pre-study of new electrical coupling between train cars." Thesis, Uppsala universitet, Signaler och System, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-167452.
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This study is meant to be an initial study of the possibility to replace the discrete control signal wires over the electrical coupler between train cars with a data bus system. The reason for this is that the electrical coupler is large and heavy due to the high amount of contacts it contains. It is also a problem for manufacturers who are upgrading an existing fleet and need to transfer more signals through a coupler with no spare contacts to use. Except the control signals there are also Ethernet and power signals in the electrical coupler. Some trains also use a bus system for control signals and/or signals containing a large amount of data such as passenger information.This report gives a presentation of some common ways to distribute electrical signals throughout a train used by most manufacturers. It also presents some design recommendations for a system that would collect existing signals to a bus system and two different design proposals that should be considered if such a system is to be developed. The study shows that there are already systems on the market for transferringcontrol signals over a bus but they are more aimed for trains under construction. Forthis reason a new bus system would only be suitable for upgrading existing couplersto free up space in the electrical coupler unit.
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Sanderson, Josh. "Hierarchical Modulation Detection of Underwater Acoustic Communication Signals Through Maximum Likelihood Combining." Wright State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=wright1410872323.
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Colosimo, Joseph William. "Doppler channel emulation of high-bandwidth signals." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/85698.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (page 97).<br>The Airborne Networks Group at MIT Lincoln Laboratory has funded the construction of a channel emulator capable of applying, in real-time, environmental models to communications equipment in order to test the robustness of new wireless communications algorithms in development. Specific design goals for the new emulator included support for higher bandwidth capabilities than commercial channel emulators and the creation of a flexible framework for future implementation of more complex channel models. Following construction of the emulator's framework, a module capable of applying Doppler shifting to the input signal was created and tested using DVB-S2 satellite modems. Testing not only verified the functionality of the emulator but also showed that DVB-S2 modems are unequipped to handle the continuous spectral frequency shifts due to the Doppler effect. The emulator framework has considerable room for growth, both in terms of implementing new channel transformation models as well as the re-implementation of the emulator on custom hardware for emulation of channels with wider bandwidths, more complex noise sources, or platform-dependent spatial blockage effects.<br>by Joseph William Colosimo.<br>M. Eng.
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Ju, Peter M. (Peter Ming-Wei) 1977. "Classification of finger gestures from myoelectric signals." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/9074.
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Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.<br>Includes bibliographical references (p. 73-75).<br>Electromyographic signals may provide an important new class of user interface for consumer electronics. In order to make such interfaces effective, it will be crucial to map EMG signals to user gestures in real time. The mapping from signals to gestures will vary from user to user, so it must be acquired adaptively. In this thesis, I describe and compare three methods for static classification of EMG signals. I then go on to explore methods for adapting the classifiers over time and for sequential analysis of the gesture stream by combining the static classification algorithm with a hidden Markov model. I conclude with an evaluation of the combined model on an unsegmented stream of gestures.<br>by Peter M. Ju.<br>S.B.and M.Eng.
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Wornell, Gregory W. "Synthesis, analysis, and processing of fractal signals." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/13465.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1991.<br>Includes bibliographical references (leaves 234-239).<br>by Gregory Wayne Wornell.<br>Ph.D.
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Zaramba, Nedas. "Kalbos signalų sintezė." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2005. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2005~D_20050614_132359-58657.
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In the contemporary world of techniques, voice technologies, such as speech recognition, synthesis of speech signals, and their combined versions, acquire more and more significance. If we had a good synthesizer, we could use it widely. An example could be the reading of electronic books in voice, etc.
Speech synthesizers of an older generation were quite primitive. A modern synthesis machine is not only able to read the text evenly, but to convey the emotionality as well. Speech synthesizer can raise a tone, dictate a question, and synthesize a voice of a desired timbre and speed. These features considerably enrich the speech synthesized.
The aim of the research paper is to analyze the operation principles of the present speech signal synthesizers and to select the type of synthesis according to the quality indicators; prior to the compilation of Lithuanian sound set, to analyze the basics of phonetics. The features of phonemes and diphones are examined in the paper. The final result of the work is the sound set of Lithuanian language incorporating the phonemes and diphones. Synthesizer of Lithuanian language may be developed using this sound set. To implement this work, the program PRAAT was used. This software was selected due to its flexibility in the acoustic analysis of speech signals.
The paper includes:
1. The analysis of general functional diagram of speech synthesis by text as well as the principles of concatenate synthesis.
2. Compilation and analysis of the... [to full text]
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Shikhaliev, Azer P. "Techniques for Adaptive Signal Detection." The Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1610123085674943.
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Pu, J. "Electrical signals control the establishment of cell polarity, tumour metastasis and wound healing." Thesis, University of Aberdeen, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.590979.
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Endogenous direct-current electric fields (EFs) play significant roles in biological and pathological processes. In this thesis I will discuss how an applied EF affects cell polarity, tumour metastasis, wound healing and provide some insights to the underlying molecular mechanisms. Directional cell migration requires proper cell polarization. The redistribution of the Golgi apparatus is a critical event in cellular polarisation. Direct current EFs as low as 0.3 V/cm induces Golgi polarization and directed cell migration. The Golgi polarizes at the same time as cells change morphology and migrate directionally in response to an electric field. Golgi polarization in turn significantly reinforces and maintains optimal electrotaxis. PKC/PI3K-GSK-3β signalling is required to promote Golgi polarization and control the direction of cell protrusion. Development of breast cancer is accompanied by electrical depolarization of the tumour epithelial cells. Applied electric fields indeed induce increased speed and directional migration of the highly metastatic cancer cells. EFs enhanced directional migration depends on EGFR/ErbB1 expression levels. Inhibition of ErbB1 activity completely abolished the directional response of tumour cells to an electric field. EFs could be the earliest signal epithelia receive to initiate directional migration and healing. Using a single cell model and a monolayer wound healing model <i>in vitro</i>, we found that a physiological EF overrides other guidance cues. When wound healing required cells to move towards the anode, they failed to do so. By contrast they were repelled and the wound opened up. This suggests that endogenous EFs may play much more important roles in re-epithelialization in wound healing.
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Gray, Martha Lane. "Physical regulation of epiphyseal cartilage biosynthesis : responses to electrical, mechanical, and chemical signals." Thesis, Massachusetts Institute of Technology, 1986. http://hdl.handle.net/1721.1/17205.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Harvard-MIT Division of Health Sciences and Technology Program in Medical Engineering and Medical Physics, 1986.<br>MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE.<br>Bibliography: leaves 194-205.<br>by Martha Lane Gray.<br>Ph.D.
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Yao, Bing. "ANALYSIS OF ELECTRICAL AND MAGNETIC BIO-SIGNALS ASSOCIATED WITH MOTOR PERFORMANCE AND FATIGUE." Case Western Reserve University School of Graduate Studies / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=case1140813534.
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Shaeboub, Abdulkarim. "The monitoring of induction machines using electrical signals from the variable speed drive." Thesis, University of Huddersfield, 2018. http://eprints.hud.ac.uk/id/eprint/34555/.
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Induction motors are the most widely used industrial prime movers, mainly because of their simple yet powerful construction, ergonomic adaptability, rugged and highly robust structure combined with high reliability. However, under extreme and complex operations, such motors are subject to premature faults, which can be more significant when variable speed drive (VSDs) are used, due to the presence of more voltage harmonics, spikes and increases in operating temperature. In addition, VSD based systems also cause more noise in measured instantaneous current signals. These make it more difficult to investigate and accurately diagnose system faults in order to keep VSD based motors operating at an optimal level and avoid excessive energy consumption and damage to system. However, insufficient work has been carried out exploring fault diagnosis using terminal voltage and motor current signals of VSD motors which are increasingly used in industry. To fill these gaps, this thesis investigates the detection of stator and rotor faults (i.e. shorted turn faults, open-circuit faults, broken rotor bars, and stator winding asymmetry combined with broken rotor bar faults) using electrical signals from VSDs under different loads and different speeds conditions. Evaluation results show that under open loop control mode, both stator and rotor faults cause an increase in the amplitude of sidebands of the motor current signature. However, no changes were found that could be used for fault detection in the motor voltage signature with respect to open loop control mode. This is because, when the drive is in open-loop operation, there is no feedback to the drive and torque oscillations modulate the motor current only. The V/Hz ratio is kept constant even when the slip changes either due to the load or the fault. On the other hand, the increase in the sideband amplitude can be observed in both the current and voltage signals under the sensorless control mode with the voltage spectrum demonstrating a slightly better performance than the motor current spectrum, because the VSD regulates the voltage to adapt changes in the electromagnetic torque caused by the faults. The comparative results between current and voltage spectra under both control modes show that the sensorless control gives more reliable diagnosis. In order to monitor the condition of electrical drives accuratly and effectively, demodulation analysis such as modulation signal bispectrum (MSB) of the electrical signals from the VSDs has been explored extensively in this thesis to detect and diagnose different motor faults. MSB analysis has been shown to provide good noise reduction, and more accurate and reliable diagnosis. It gives a more correct indication of the fault severity and fault location for all operating conditions. This study also examines detecting and diagnosing the effect of an asymmetric stator winding combined with broken rotor bar (BRB) faults under the sensorless operation mode. It examines the effectiveness of conventional diagnostic features in both motor current and voltage signals using power spectrum (PS) and MSB analysis. The obtained results show that the combined fault causes an additional increase in the sideband amplitude and this increase can be observed in both the current and voltage signals. The MSB diagnosis based on the voltage signals is more sensitive to detect motor faults at lower loads compared with that of current signals. Moreover, this research presented a new method based on MSB sideband estimation (MSB-SE). It is shown that using MSB-SE, the sidebands due to weak fault signatures can be quantified more accurately, which results in more consistent detection and accurate diagnosis of the fault severity.
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Lee, Li 1975. "Distributed signal processing." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86436.
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Eldar, Yonina Chana 1973. "Quantum signal processing." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/16805.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2002.<br>Includes bibliographical references (p. 337-346).<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Quantum signal processing (QSP) as formulated in this thesis, borrows from the formalism and principles of quantum mechanics and some of its interesting axioms and constraints, leading to a novel paradigm for signal processing with applications in areas ranging from frame theory, quantization and sampling methods to detection, parameter estimation, covariance shaping and multiuser wireless communication systems. The QSP framework is aimed at developing new or modifying existing signal processing algorithms by drawing a parallel between quantum mechanical measurements and signal processing algorithms, and by exploiting the rich mathematical structure of quantum mechanics, but not requiring a physical implementation based on quantum mechanics. This framework provides a unifying conceptual structure for a variety of traditional processing techniques, and a precise mathematical setting for developing generalizations and extensions of algorithms. Emulating the probabilistic nature of quantum mechanics in the QSP framework gives rise to probabilistic and randomized algorithms. As an example we introduce a probabilistic quantizer and derive its statistical properties. Exploiting the concept of generalized quantum measurements we develop frame-theoretical analogues of various quantum-mechanical concepts and results, as well as new classes of frames including oblique frame expansions, that are then applied to the development of a general framework for sampling in arbitrary spaces. Building upon the problem of optimal quantum measurement design, we develop and discuss applications of optimal methods that construct a set of vectors.<br>(cont.) We demonstrate that, even for problems without inherent inner product constraints, imposing such constraints in combination with least-squares inner product shaping leads to interesting processing techniques that often exhibit improved performance over traditional methods. In particular, we formulate a new viewpoint toward matched filter detection that leads to the notion of minimum mean-squared error covariance shaping. Using this concept we develop an effective linear estimator for the unknown parameters in a linear model, referred to as the covariance shaping least-squares estimator. Applying this estimator to a multiuser wireless setting, we derive an efficient covariance shaping multiuser receiver for suppressing interference in multiuser communication systems.<br>by Yonina Chana Eldar.<br>Ph.D.
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Lam, Warren Michael. "Modeling algorithms for a class of fractal signals." Thesis, Massachusetts Institute of Technology, 1992. http://hdl.handle.net/1721.1/31034.
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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1992.<br>Includes bibliographical references (leaves 86-87).<br>by Warren Michael Lam.<br>M.S.
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Blalock, Davis W. (Davis Whitaker). "Feature Flocks : accurate pattern discovery in multivariate signals." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/105682.
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Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 81-85).<br>Thanks to the rise of wearable and connected devices, sensor-generated time series comprise a large and growing fraction of the world's data. Unfortunately, extracting value from this data can be challenging, since sensors can only report low-level signals (e.g., acceleration), not the high-level phenomena that are typically of interest (e.g., gestures). We introduce a technique to bridge this gap by automatically learning to identify real-world events in low-level data with no human labeling. By identifying "flocks" of features that repeat in the same temporal arrangement, we learn to recognize such diverse phenomena as human actions, power consumption patterns, and spoken words with up to 96% precision and recall. Our method is fast enough to run in real time and assumes only minimal knowledge of which variables are relevant or how long patterns are. Our evalation uses numerous publicly available datasets and over 1 million samples of sensor data in which we manually labeled ground truth.<br>by Davis W. Blalock.<br>S.M.
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Papadopoulos, Haralabos Christos 1968. "Efficient digital encoding and estimation of noisy signals." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/9957.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.<br>Includes bibliographical references (p. 163-165).<br>by Haralabos Christos Papadopoulos.<br>Ph.D.
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Kim, Frank Seong-Huhn. "Converting EKG signals into 3-D stereo sound." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/35955.
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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.<br>Includes bibliographical references (leaves 85-86).<br>by Frank Seong-Huhn Kim.<br>M.S.
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Yue, Shichao. "Extracting multi-person respiration from entangled RF signals." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117817.
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Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 53-56).<br>Recent advances in wireless systems have demonstrated the possibility of tracking a person's respiration using the RF signals that bounce off her body. The resulting breathing signal can be used to infer the person's sleep quality and stages; it also allows for monitoring sleep apnea and other sleep disordered breathing; all without any body contact. Unfortunately however past work fails when people are close to each other, e.g., a couple sharing the same bed. In this case, the breathing signals of nearby individuals interfere with each other and super-impose in the received signal. This thesis presents DeepSleep, the first RF-based respiration monitoring system that can recover the breathing signals of multiple individuals even when they are separated by zero distance. To design DeepSleep, we model interference due to multiple reflected RF signals and demonstrate that the original breathing can be recovered via independent component analysis. We design a full system that eliminates interference and recovers the original breathing signals. We empirically evaluate DeepSleep using 21 nights of sleep and over 150 hours of data from 13 couples who share the bed. Our results show that DeepSleep is very accurate. Specifically, the differences between the breathing signals it recovers and the ground truth are on par with the difference between the same breathing signal measured at the person's chest and belly. Thesis Supervisor: Dina Katabi<br>by Shichao Yue.<br>S.M.
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Ng, Trina Tsao-Tin. "Domain transformations for optical telecommunications signals." Thesis, University of Southampton, 2010. https://eprints.soton.ac.uk/301294/.
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In this thesis, the transformation of optical telecommunication signal waveforms between the temporal and spectral domains is investigated. Temporal optical Fourier transformations (TOFTs) are presented with the primary aim of mitigating distortions in high repetition rate telecommunication signals, by transferring them from the temporal domain into the frequency domain. Development of TOFT is extended to aid their suitability for other applications also. The TOFT is based on inducing cross-phase modulation on the signal to be transformed, using shaped parabolic pulses as the pump. To demonstrate the technique, various methods of generating parabolic pulses are investigated and considered for their suitability for TOFTs. Firstly, parabolic pulses are generated in a nonlinear fashion exploiting their natural evolution in a normally dispersive fibre. Compensation is performed on timing jitter signals using this method. In another configuration, parabolic pulses are generated with a superstructured fibre Bragg grating. The passive nature and the chirp free parabolics generated by the grating enabled greater flexibility in the experimental parameters thus improving the fidelity of the TOFT. Compensation of pulses distorted by second and third order dispersion is demonstrated. Unexpected results in the first two TOFT experiments led to further analysis and the derivation of the conditions for a complete TOFT. Sophisticated reconfigurable filters are used to convert an optical frequency comb (OFC) into one or more simultaneous pulse sources, each with a configurable shape and phase profile. Pulses generated using the OFC and reconfigurable filter are used to experimentally verify the new theory. The thesis also includes a presentation of a linear frequency resolved optical gating technique. The versatility of the technique was demonstrated through the characterisation of many of the pulses generated in this thesis, providing insight to their time-frequency domain relationships.
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Meehan, Timothy J. "Joint demodulation of low-entropy narrow band cochannel signals." Thesis, Monterey, Calif. : Naval Postgraduate School, 2006. http://bosun.nps.edu/uhtbin/hyperion.exe/06Dec%5FMeehan%5FPhD.pdf.
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Thesis (Ph.D. in Electrical Engineering)--Naval Postgraduate School, December 2006.<br>Dissertation supervisor(s): Frank E. Kragh. "December 2006." Includes bibliographical references (p. 167-177). Also available in print.
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Tunca, Yasar. "Partially coherent detection of PSK signals in Rician channels." Thesis, University of Ottawa (Canada), 1992. http://hdl.handle.net/10393/7820.
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Coherent detection which has the best performance in ideal channels suffers in environments where there is significant phase noise (e.g. fading channels). In this thesis, we developed channel models for noisy phase reference and Rician fading channels and assuming that partially coherent detection could be an alternative, we derived metric expressions for partially coherent detection of signals in general and applied it to PSK signals. Simulation programs were run using the developed channel models and the results were compared to other detection schemes under same conditions.