Department: Electrical Engineering ![[clear]](close-x.png "Remove this limiter")
47 matches in the database.
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1.
Alemayehu, Andargachew Desta.
Microwave Frequency Thin BST Film Based Tunable Shunt and Series Interdigital Capacitor Device Design.
Degree: MS, Electrical Engineering, 2011, University of Dayton
► This research covers novel interdigital capacitor designs and explores the different parameters…
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▼ This research covers novel interdigital capacitor designs and explores the different parameters affecting the electrical characteristics of the devices. Interdigitated capacitors were designed using parallel electrodes in series and in shunt configurations. The main purpose of these devices is to enhance the tunability as compared to conventional IDCs while retaining the high voltage bias capability. The new devices were designed and simulated using Advance Wireless Research (AWR) software, fabricated using PLD technique, tested and analyzed using HP8720 Network analyzer and AWR software respectively. During this thesis, we successfully demonstrated the new parallel plate IDC devices with higher tunability and high voltage bias capability.
Advisors/Committee Members: Subramanyam, Guru.
Subjects: Electrical Engineering; Materials Science
Keywords: Tunable devices; BST film, Series and Shunt interdigital; Interdigital Capacitor; Novel interdigital device; Novel IDC design; IDC; resonant
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2.
Alex, Ann Theja.
Local Alignment of Gradient Features for Face Photo and Face Sketch Recognition.
Degree: MS, Electrical Engineering, 2012, University of Dayton
► Automatic recognition of human faces (face photo recognition) irrespective of the expression…
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▼ Automatic recognition of human faces (face photo recognition) irrespective of the expression variations and occlusions is a challenging problem. In the proposed technique, the edges of a face are identified, and a feature string is created from edge pixels. This forms a symbolic descriptor corresponding to the edge image referred to as 'edge-string'. The 'edge-strings' are then compared using the Smith-Waterman algorithm to match them. The class corresponding to each image is identified based on the number of string primitives that match. This method needs only a single training image per class. The proposed technique is also applicable to face sketch recognition. In face sketch recognition, a sketch drawn based on the descriptions of the victims or witnesses is compared against the photos in the mug shot database to facilitate a faster investigation. The effectiveness of the proposed method is compared with state-of-the-art algorithms on several databases. The method is observed to give promising results for both face photo recognition and face sketch recognition.
Advisors/Committee Members: Asari, Vijayan K.
Subjects: Computer Engineering; Computer Science; Electrical Engineering
Keywords: Face recognition; Face sketch recognition; String Matching; Smith Waterman Algorithm; Edge features; Biometrics
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3.
Al Issa, Huthaifa A.
Position-adaptive Direction Finding for Multi-platform RF Emitter Localization using Extremum Seeking Control.
Degree: PhD, Electrical Engineering, 2012, University of Dayton
► In recent years there has been growing interest in Ad-hoc and Wireless…
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▼ In recent years there has been growing interest in Ad-hoc and Wireless Sensor Networks (WSNs) for a variety of indoor applications. Localization information in these networks is an enabling technology and in some applications it is the parameter of primary importance. WSNs are being used in a variety of ways - from reconnaissance and detection in military to biomedical applications and a wide variety of commercial endeavors. In recent years, position-based services have become more important. Thus, recent developments in communications and RF technology have enabled system concept formulations and designs for low-cost radar systems using state-of-the-art software radio modules, which are capable of local processing and wireless communication, a reality. Such nodes are called as sensor nodes. Each sensor node is capable of only a limited amount of processing. This research focused on the modeling and implementation of distributed, mobile radar sensor networks. In particular, we worked on the problem of Position-Adaptive Direction Finding (PADF), to determine the location of a non-collaborative transmitter, possibly hidden within a structure, by using a team of cooperative intelligent sensor networks. Our purpose is to further develop and refine position-adaptive RF sensing techniques based on the measurement and estimation of RF scattering metrics. Topics planned for this entrepreneurial research project are focused on the investigation, analysis/simulation, and development of real time multi-model (i.e., complex multipath) environments scattering decompositions for PADF geometries. PADF is based on the formulation and investigation of path-loss based RF scattering metrics (i.e., estimation of distributed Path Loss Exponent, or PLE) that are measured and estimated across multiple platforms in order to enable the robotic/intelligent position-adaptation (or self-adjustment) of the location of each platform. We provide a summary of recent experimental results in localization of a non-cooperative sensor node using static and mobile sensor networks. In this study we used IRIS wireless sensor nodes. In order to localize the transmitter, we used the Received Signal Strength Indicator (RSSI) data to approximate distance from the transmitter to the revolving receivers. We provided an algorithm for on-line estimation of the PLE that is used in modeling the distance based on RSSI measurements. The emitter position estimation is calculated based on surrounding sensors RSSI values using Least-Square Estimation (LSE). The PADF has been tested on a number of different configurations in the laboratory via the design and implementation of four IRIS wireless sensor nodes as receivers and one hidden sensor as a transmitter during the localization phase. The robustness of detecting the transmitter's position is initiated by getting the RSSI data through experiments and then data manipulation in MATLAB will determine the robustness of each node and ultimately that of each configuration. The parameters that are used in the functions are the median values of RSSI and rms values. From the result it is determined which configurations possess high robustness. High values obtained from the robustness function indicate high robustness, while low values indicate lower robustness. Finally, we present the experimental performance analysis on the application aspect. We apply Extremum Seeking Control (ESC) schemes by using the swarm seeking problem, where the goal is to design a control law for each individual sensor that can minimize the error metric by adapting the sensor positions in real-time, thereby minimizing the unknown estimation error. As a result we achieved source seeking and collision avoidance of the entire group of the sensor positions.
Advisors/Committee Members: Ordonez, Raul.
Subjects: Electrical Engineering
Keywords: Wireless Sensor Networks; Path Loss Exponent; Localization; Received Signal Strength Indicator; Robustness; Extremum Seeking Control
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4.
Al-saedi, Mohammed Abdullah.
Examination of Acousto-Optic Chaos and Application to RF Signal Encryption and Recovery.
Degree: PhD, Electrical Engineering, 2012, University of Dayton
► In communication systems, there are different coding schemes such as linear predictive…
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▼ In communication systems, there are different coding schemes such as linear predictive coding, block coding, and veterbi coding that can be used to encode data for different purposes. One of the techniques to encode/encrypt data for security purposes is to use chaos. Chaotic systems can be manipulated, via arbitrarily small time-dependent perturbations, to generate controlled chaotic orbits whose symbolic representation corresponds to the encoding of a desirable message. An advantage of this type of communication strategy is that the nonlinear chaotic oscillator that generates the wave form for transmission can remain simple and efficient, while all the necessary electronics controlling encoding of the signal remain at the low-powered microelectronic level. Moreover, since the chaotic dynamics can be recovered from a chaotic signal, which in principle can be noisy, by using standard dynamical data analysis techniques, communicating with chaos is also more robust and better behaved against channel noise. Signal encryption and recovery using chaotic optical waves has been a subject of active research in the past 10 years. Since an acousto-optic Bragg cell with zeroth- and first-order feedback exhibits chaotic behavior past the threshold for bistability, such a system was examined for possible chaotic encryption using a low-amplitude sinusoidal signal applied via the bias input of the sound cell driver. Subsequent recovery of the message signal was carried out via a heterodyne strategy employing a locally generated chaotic carrier, with threshold parameters matched to the transmitting Bragg cell. The simulation results, though encouraging and extend to the following (i) increasing the chaos frequency using appropriate parameter control; (ii) carefully examining the system sensitivity to three system parameters, viz., feedback delay, feedback gain, and dc bias level; (iii) examine signal recoverability relative to shifts in the three parameters mentioned above relative to the transmitter; and (iv) determining the robustness of such a system relative to the primary transmitter parameters. Additionally, we consider also the effect of the additive bandpass noise (obtained from white Gaussian noise in the simulator) on signal recovery in such a system from a performance standpoint. It is also conjectured that signal recovery can be effected by passing the modulated light through a second sound cell in a matched chaotic regime. Since an acousto-optic Bragg cell with zeroth- and first-order feedback exhibits chaotic behavior past the threshold for bistability, such a system was recently examined for possible chaotic encryption of simple messages such as a low-amplitude sinusoidal signal applied via the bias input of the sound cell driver. Also, the nonlinear dynamics of the A-O feedback including the effect of the parameters such as feedback gain, dc bias, and time delay are examined in some detail taking into consideration that the intensity amplitude equals 1 and I1(0) = 0. The results obtained via computer simulation reveal variety of interesting dynamics including bistability, bifurcation, and chaos. Also, Lyapunov exponents have been generated for variety of parameters. However, Lyapunov and Bifurcation maps with varying the three parameters are going to vary if the light intensity and I1(0) were varied.
Advisors/Committee Members: Chatterjee, Monish.
Subjects: Computer Engineering; Electrical Engineering; Engineering; Optics
Keywords: Acousto-Optics, HAOF, Bragg regime, bistability, chaos, encryption, decryption, modulation, Lyapunov exponent, bifurcation maps, chaotic bandgaps
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5.
Arroyo, Eduardo.
A Study on Muon Drift Tube Health Monitoring with a Concentration in Temperature and Gas Composition.
Degree: MS, Electrical Engineering, 2010, University of Dayton
► This thesis is focused on the temperature and gas composition aspects of…
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▼ This thesis is focused on the temperature and gas composition aspects of a Health Monitoring System for a nuclear material detection chamber powered by Muon Drift Tube arrays. This technology was developed with the purpose of providing a safer, more effective volume imaging technique to detect threat material. By using an array of these tubes to enclose a scan area, one would be able to detect the entrance and exit vectors of the muons going across in order to generate an accurate 3-D representation of the matter where colors would dictate density levels (correlating to a material’s nuclear number). Each of the tubes on the detector array have a tungsten wire going across their center and are filled with a mixture of gases that is designed to be excited by the passage of muons through the tube.A high positive potential is placed on the wire to attract electrons dislodged by the muon passage. The signal caused by the work of the electrons is then amplified, time tagged and sent to a computer system for 3-D image generation.The relevance of the research subject comes from the fact that the performance of these detectors is very sensitive to variations in both physical and environmental conditions in terms of accuracy and consistency in operation. These variables include, but are not limited to, conditions such as temperature, pressure, humidity, gas composition, magnetic field, wire gravitational effects and other factors that come from detector aging. As a result of these constraints, it is essential to understand the behavior of the detector when affected by these conditions to try to develop a design in which the detector can maintain consistent performance. Through research and experimentation one can generate enough data to not only analyze detector performance under these variables but also to use the data to develop a control system that ‘learns’ to adjust through automatic configuration of the electronics. Nuclear terrorism ranks high on the top threats to humanity in the next century; muon tomography technology represents a leap in a field of ever increasing importance since it not only presents a safer scanning mechanism but is also able to detect threat material hidden in dense containers. Scientists agree that the technology currently used at US borders, which mainly involves x-ray and gamma detectors, is inefficient for detecting nuclear materials isolated with layers of lead or steel. Any terrorist organization that has the technology to represent a nuclear threat in the future will ultimately also have the resources to develop better ways to hide their material from detection. This technology, when implemented correctly, could ultimately help upset those efforts. With such an important duty on its shoulders and millions of dollars ultimately spent to implement the technology, it is essential to guarantee the lowest percentage of detector error regardless of variations in its physical and environmental conditions.
Advisors/Committee Members: Weber, John.
Subjects: Chemistry; Electrical engineering; Engineering; Physics
Keywords: Muon, Drift Tube, Nuclear, Detector, Garfield
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6.
Aspiras, Theus H.
Emotion Recognition using Spatiotemporal Analysis of Electroencephalographic Signals.
Degree: MS, Electrical Engineering, 2012, University of Dayton
► Emotion recognition using electroencephalographic (EEG) recordings is a new area of research…
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▼ Emotion recognition using electroencephalographic (EEG) recordings is a new area of research which focuses on recognition of emotional states of mind rather than impulsive responses. EEG recordings are found useful for the detection of emotions through monitoring the emotion characteristics of spatiotemporal variations of activations inside the brain. To distinguish between different emotions using EEG data, we need to provide specific spectral descriptors as features to quantify these spatiotemporal variations. We propose several new features, namely Normalized Root Mean Square (NRMS), Absolute Logarithm Normalized Root Mean Square (ALRMS), Logarithmic Power (LP), Normalized Logarithmic Power (NLP), and Absolute Logarithm Normalized Logarithmic Power (ALNLP) for the classification of emotions. A protocol has been established to elicit five distinct emotions: joy, sadness, disgust, fear, surprise, and neutral. EEG signals are collected using a 256-channel system, preprocessed using band-pass filters and a Laplacian Montage, and decomposed into five frequency bands using Discrete Wavelet Transform. The decomposed signals are transformed into different spectral descriptors and are classified using a two-layer Multilayer Perceptron (MLP) neural network. The Logarithmic Power descriptor produces the highest recognition rates, 91.82% and 94.27% recognition for two different experiments, which is more than 2% higher than when using other features.
Advisors/Committee Members: Asari, Vijayan.
Subjects: Computer Engineering; Electrical Engineering; Engineering; Neurosciences; Psychology
Keywords: Emotion Recognition; Electroencephalography; Wavelet Decomposition; Multilayer Perceptron; Laplacian Montage; International Affective Picture System
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7.
Aylo, Rola.
Wave Propagation in Negative Index Materials.
Degree: PhD, Electrical Engineering, 2010, University of Dayton
► Properties of electromagnetic propagation in materials with negative permittivities and permeabilities were…
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▼ Properties of electromagnetic propagation in materials with negative permittivities and permeabilities were first studied in 1968. In such metamaterials, the electric field vector, the magnetic field vector, and the propagation vector form a left hand triad, thus the name left hand materials. Research in this area was practically non-existent, until about 10 years ago, a composite material consisting of periodic metallic rods and split-ring resonators showed left-handed properties. Because the dimension of the constituents of the metamaterial are small compared to the operating wavelength, it is possible to describe the electromagnetic properties of the composite using the concept of effective permittivity and permeability. In this dissertation, the basic properties of electromagnetic propagation through homogenous left hand materials are first studied. Many of the basic properties of left hand materials are in contrast to those in right hand materials, viz., negative refraction, perfect lensing, and the inverse Doppler effect. Dispersion relations are used to study wave propagation in negative index materials. For the first time to the best of our knowledge, we show that a reduced dispersion relation, obtained from the frequency dependence of the propagation constant by neglecting a linear frequency dependent term, obeys causality. Causality of the propagation constant enables us to use a novel and simple operator formalism approach to derive the underlying partial differential equations for baseband and envelope wave propagation. Various tools for understanding and characterizing left-handed materials are thereafter presented. The transfer matrix method is used to analyze periodic and random structures composed of positive and negative index materials. By random structures we mean randomness in layer position, index of refraction, and thickness. As an application of alternating periodic negative index and positive index structures, we propose a novel sensor using the zero average gap that only appears in such structures which has different properties from the usual Bragg gap occurring in alternating positive index structures. Also in this dissertation, we propose a novel negative index material in the visible range based on nanoparticle dispersed liquid crystal cells. The extended Maxwell Garnett theory, which is combination of the regular Maxwell Garnett and Mie scattering theories, is used to find the effective refractive index of the proposed cell. Nanoparticle dispersed liquid crystal cells can also be used as plasmonic sensors. A theoretical study of such sensors is presented. Finally, fabrication and testing of such cells is proposed and initial progress in fabrication is reported. The final assembly and testing of nanoparticle dispersed liquid crystal cells constitute ongoing and future work.
Advisors/Committee Members: Banerjee, Partha.
Subjects: Electrical engineering; Optics
Keywords: metamaterials, multilayer structure, effective medium theory
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8.
Ballard, Brett S.
Feature Based Image Mosaicing using Regions of Interest for Wide Area Surveillance Camera Arrays with Known Camera Ordering.
Degree: MS, Electrical Engineering, 2011, University of Dayton
► Today, modern surveillance systems utilizing camera arrays can capture several square miles…
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▼ Today, modern surveillance systems utilizing camera arrays can capture several square miles of ground activity at high resolution from a single aircraft. A camera array uses multiple cameras to capture images synchronously with partial overlap between cameras' fields of view. This allows a wide area to be monitored continuously in real time by image analysts or processed for information such as object identification and location tracking. The task of combining these images from each individual camera into one large image containing all of the images' views of the scene activity is commonly called image mosaicing in the field of computer vision. Though the process of image mosaicing is not new, what makes image mosaicing a topic of current research is the difficulty and variety of both problems and solutions. The objective of this thesis is to demonstrate the most suitable system to mosaicing images captured by wide area surveillance camera arrays with known camera ordering by using regions of interest combined with a feature based approach. The proposed system utilizes algorithms for feature extraction, matching, and estimation. The key difference between the proposed mosaicing system and prior successful mosaicing systems within other application domains is the use of known camera ordering. In many previously researched mosaicing systems no assumption is made for camera order, and in fact in some applications there is no assumption that images may even be viewing the same scene at all. However, for applications involving wide area surveillance camera arrays these assumptions are perfectly valid. This allows bounded regions of interest near the appropriate image borders to be used which is demonstrated in the proposed system to increase performance in both pixel accuracy and mosaic computation times over the more generalized mosaicing approach.
Advisors/Committee Members: Balster, Eric.
Subjects: Electrical Engineering; Remote Sensing; Scientific Imaging
Keywords: regions of interest; roi; known camera ordering; image mosaicing; feature based homography; image stitching; stereo computer vision; wide area surveillance; camera array
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9.
Bandaru, Mohan Ujwal.
Modelling and the Study of the Memristor.
Degree: MS, Electrical Engineering, 2012, University of Dayton
► Till date the circuitry world has known three fundamental circuit elements -…
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▼ Till date the circuitry world has known three fundamental circuit elements - capacitor, resistor and inductor. These circuit elements are dened by the relation between two of the four fundamental circuit variables- current, voltage, charge and flux. Way back in 1971, Prof. Leon Chua proposed on the grounds of symmetry that there should be a fourth fundamental circuit element which gives the relation between flux and charge. He named this the memristor, which is the short of memory resistor. This theory was then practically modeled, in May 2008 when the researchers at HP Labs published a paper announcing a model for a physical realization of a memristor. This report mainly focuses on the model of memristor and its applications. All the simulation results are studied using LTSpice.
Advisors/Committee Members: Loomis, John.
Subjects: Electrical Engineering; Electromagnetics
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10.
Brys, Brandon J.
Image Restoration in the Presence of Bad Pixels.
Degree: MS, Electrical Engineering, 2010, University of Dayton
► Spatially varying temporal noise can occur in imaging sensors from nonuniform responsivity…
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▼ Spatially varying temporal noise can occur in imaging sensors from nonuniform responsivity of the detectors in the focal plane detector array. Furthermore, some pixels can have extreme responsivities or simply be unresponsive altogether. Such "bad pixels" must be detected and addressed to provide the best possible imagery from a given sensor. Restoration in the presence of bad pixels is a particularly important problem in infrared imaging systems, but it is also an issue with many other camera systems. Bad pixels are traditionally treated by some form of replacement. Rather than performing a simple pixel replacement followed by traditional image restoration, we believe that a superior method of performing restoration in the presence of bad pixels is to perform the restoration and bad pixel replacement jointly. This way, we are able to exploit knowledge of each pixel's characteristics in the restoration process. When a simple pixel replacement method is used, knowledge of which pixel was originally bad is often lost and not exploited in any subsequent image restoration. In this thesis we propose and compare two methods for scene-based bad pixel detection. We also adapt the FIR adaptive Wiener Filter (AWF) to perform image restoration in the presence of bad pixels on other forms of spatially varying noise. The AWF estimates each pixel using a weighted sum of neighboring pixel values. The weights are determined based on spatially varying autocorrelation models which may use specific knowledge of each pixel's noise characteristics. We propose a fast version of the AWF that is able to handle the bad pixels by using pre-computed weights in a table look-up process. We also propose a modified version of the Non-Local Means (NLM) filter that is robust in handling bad pixels, as it provides background noise reduction. We quantitatively and subjectively compare the performance of the AWF and NLM methods along with several other benchmark restoration methods using simulated images with spatially varying noise and bad pixels. We use both simulated and real infrared imagery to test the proposed algorithms. A computational complexity analysis is also provided to provide further insight into the comparison between the AWF and NLM methods.
Advisors/Committee Members: Hardie, Russell.
Subjects: Electrical engineering
Keywords: infrared imagery, restoration filters, bad pixels, spatially varying noise, photodetectors
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11.
Cheng, Wu.
Corrupted Image Quality Assessment.
Degree: MS, Electrical Engineering, 2012, University of Dayton
► We propose a foundation for assessing visual quality with "corrupted reference"(CR-QA) -…
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▼ We propose a foundation for assessing visual quality with "corrupted reference"(CR-QA) - a new quality assessment(QA) paradigm for reasoning about human vision and image restoration problems jointly. The visual quality of a processed image signal is assessed relative to an ideal reference image (not provided) with the help of observed image. This is in contrast to today's QAs, which are optimized for a "post-hoc" usage (process first, assess quality second) and are unequipped to handle the assessment of the processed data relative to the ideal reference that exist only in theory and not in practice.
Advisors/Committee Members: Hirakawa, Keigo.
Subjects: Engineering; Statistics
Keywords: corrupted reference; CR-QA; image quality; image assessment; image restoration
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12.
Corwin, Michael Thomas.
Inductively Loading a Half Width Leaky Wave Antenna to Control the Main Beam Direction.
Degree: MS, Electrical Engineering, 2012, University of Dayton
► The half width leaky wave antenna uses shorting vias to suppress the…
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▼ The half width leaky wave antenna uses shorting vias to suppress the dominant mode by forming a phase reversal at the symmetrical center of the antenna. The shorting vias causes a small inductance formed by the shorting vias that cause a variation in the main beam direction. Prior to this research the shorting vias had been assumed to form a perfect short and caused errors in the transverse resonance method calculations and main beam direction estimates. Once the spacing of the shorting vias becomes too wide as related to the wave length the dominant mode is no longer suppressed and the transverse resonance method does not properly approximate the performance of the antenna. The results are modeled in the transverse resonance method then corroborated using a Finite Element Boundary Integral and Finite Integration Technique computational electromagnetic methods.
Advisors/Committee Members: Penno, Robert.
Subjects: Electrical Engineering
Keywords: antenna; leavy wave; inductance; transverse resonance method; microstrip
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13.
Devarakonda, SaiPrasanth.
Particle Swarm Optimization.
Degree: MS, Electrical Engineering, 2012, University of Dayton
► The particle swarm algorithm is a computational method to optimize a problem…
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▼ The particle swarm algorithm is a computational method to optimize a problem iteratively. As the neighborhood determines the sufficiency and frequency of information flow, the static and dynamic neighborhoods are discussed. The characteristics of the different methods for the selection of the algorithm for a particular problem are summarized. The performance of particle swarm optimization with dynamic neighborhood is investigated by three different methods. In the present work two more benchmark functions are tested using the algorithm. Conclusions are drawn by testing the different benchmark functions that reflect the performance of the PSO with dynamic neighborhood. And all the benchmark functions are analyzed by both Synchronous and Asynchronous PSO algorithms.
Advisors/Committee Members: Ordonez, Raul.
Subjects: Electrical Engineering; Engineering
Keywords: Synchronous; Asynchronous; Dynamic neighborhood
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14.
Foytik, Jacob D.
Locally Tuned Nonlinear Manifold for Person Independent Head Pose Estimation.
Degree: PhD, Electrical Engineering, 2011, University of Dayton
► Fine-grain head pose estimation from imagery is an essential operation for many…
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▼ Fine-grain head pose estimation from imagery is an essential operation for many human-centered systems, including pose independent face recognition and human-computer interaction systems. It is only recently that estimation systems have evolved past a coarse level classification of pose and concentrated on fine-grain estimation. In particular, the state of the art of such systems consists of nonlinear manifold embedding techniques, such as Locally Linear Embedding and Isomap, that capture the intrinsic relationship of a pose varying face dataset. The success of these solutions can be attributed to the acknowledgment that image variation corresponding to pose change is nonlinear in nature. Yet, these algorithms are limited by the complexity of embedding functions that describe the relationship and provide no clear method for projecting novel data to the latent space. On the other hand, linear methods and nonlinear approximation techniques permit a simple embedding process, but lack the representational quality to globally describe the nonlinear image variation. In this dissertation, a pose estimation framework that seeks to describe the global nonlinear relationship in terms of localized linear functions is presented. A locally tuned nonlinear manifold is formulated using a two-layer system based on the assumptions that coarse pose estimation can be performed adequately using supervised linear methods, and fine pose estimation can be achieved using linear regressive functions if the scope of the pose manifold is limited. The localized linear approach results in a simplistic model for which probe input can be embedded through a cascade of linear transformations. Additionally, new methods for modeling the localized structures using feature enhanced Canonical Correlation Analysis are developed, where pose variation is regarded as a continuous variable and is represented by a manifold in feature space. The feature enhanced methods are used to identify the modes of correlation between the observed input images and the head pose angle. These techniques exploit oriented filters which serve two key purposes: (a) eliminate noise features, while boosting image elements that are associated with head pose (b) provide multiple dimensions of the input, allowing the correlation analysis process to extract more basis vectors to provide higher accuracy. A pose estimation system is implemented utilizing simple linear subspace methods, phase congruency, and Gabor features. The framework is tested using conventional test strategies and widely accepted pose-varying face databases. The proposed method is first tested using homogeneous datasets, where the training and testing face images are sampled from the same database. The generalization capabilities of the system are then tested using heterogeneous tests, where the training data is taken from a different database than the testing set. The proposed system is shown to perform fine head pose estimation with competitive accuracy when compared with state of the art nonlinear manifold methods. The results show that the system is capable of predicting head orientation in the yaw direction with as little as 3.46 degrees of error. This research is progressing to expand the multi-layer concept to the case of generalized object pose estimation and predicting pose with multiple degrees of freedom.
Advisors/Committee Members: Asari, Vijayan.
Subjects: Computer Engineering; Electrical Engineering
Keywords: Head Pose Estimation; Piecewise Linear Manifold; Pose Sensitive Representations; Coarse to Fine; Head Orientation; Phase Congruency
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15.
Han, Bing.
ACCELERATION OF SPIKING NEURAL NETWORK ON GENERAL PURPOSE GRAPHICS PROCESSORS.
Degree: MS, Electrical Engineering, 2010, University of Dayton
► There is currently a strong push in the research community to develop…
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▼ There is currently a strong push in the research community to develop biological scale implementations of neuron based vision models. Systems at this scale are computationally demanding and have generally utilized more accurate neuron models, such as the Izhikevich and Hodgkin-Huxley models, in favor of the more popular integrate and fire model. This thesis examines the feasibility of using GPGPUs for accelerating a spiking neural network based character recognition network to enable large scale neural systems. Two versions of the network utilizing the Izhikevich and Hodgkin-Huxley models are implemented. Three NVIDIA GPGPU platforms and one GPGPU cluster were examined. These include the GeForce 9800 GX2, the Tesla C1060, the Tesla S1070 platforms, and the 32-node Tesla S1070 GPGPU cluster. Our results show that the GPGPUs can provide significant speedups over conventional processors. In particular, the fastest GPGPU utilized, the Tesla S1070, provided speedups of 5.6 and 84.4 time over highly optimized implementations on the fastest CPU tested, a quad core 2.67 GHz Xeon processor, for the Izhikevich and Hodgkin Huxley models respectively. The CPU implementation utilized all four cores and the vector data parallelism offered by the processor. The results indicate that GPGPUs are well suited for this application domain. A large portion of the results presented in this thesis have been published in the April 2010 issue of Applied Optics [1].
Advisors/Committee Members: Taha, Tarek.
Subjects: Electrical engineering
Keywords: Spiking neural networks; GPGPU
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16.
Heebl, Jason Daniel.
Development and Characterization of a Tunable Resonant Shielded Loop Wireless Non-Radiative Power Transfer System.
Degree: MS, Electrical Engineering, 2011, University of Dayton
► In this thesis, the theory of coupled resonators for non-adiative wireless power…
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▼ In this thesis, the theory of coupled resonators for non-adiative wireless power transfer are explored from a lumped element circuit perspective. A basic circuit model is developed and standard circuit parameters are defined. A directly fed resonant shielded loop for wireless power transfer is presented. Basic lumped component values and circuit parameters are experimentally extracted for two resonant shielded loops. Optimal efficiency conditions are derived and used to design optimal matching networks. Matching networks are constructed and the system is tested for power transfer efficiency. Two means of producing a tunable system are explored: frequency tuned sources and dynamic matching networks. It is shown that frequency tuned systems cannot achieve maximum efficiencies. A tunable system is constructed and tested. Experimental results show excellent agreement with theory, and the ability to achieve maximum achievable efficiencies.
Advisors/Committee Members: Penno, Robert.
Subjects: Electrical Engineering; Electromagnetics; Electromagnetism; Energy; Engineering; Solid State Physics
Keywords: Wireless; Power; Transfer; WNPT; resonant; shielded loop; non-radiative; wireless power transfer; WPT
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17.
Jennings, Alan Lance.
Autonomous Motion Learning for Near Optimal Control.
Degree: PhD, Electrical Engineering, 2012, University of Dayton
► Human intelligence has appealed to the robotics community for a long time;…
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▼ Human intelligence has appealed to the robotics community for a long time; specifically, a person's ability to learn new tasks efficiently and eventually master the task. This ability is the result of decades of development as a person matures from an infant to an adult and a similar developmental period seems to be required if robots are to obtain the ability to learn and master new skills. Applying developmental stages to robotics is a field of study that has been growing in acceptance. The paradigm shift is from directly pursuing the desired task to progressively building competencies until the desired task is reached. This dissertation seeks to apply a developmental approach to autonomous optimization of robotic motions, and the methods presented extend to function shaping and parameter optimization. Humans have a limited ability to concentrate on multiple tasks at once. For robots with many degrees of freedom, human operators need a high-level interface, rather than controlling the positions of each angle. Motion primitives are scalable control signals that have repeatable, high-level results. Examples include walking, jumping or throwing where the result can be scaled in terms of speed, height or distance. Traditionally, motion primitives require extensive, robot-specific analysis making development of large databases of primitives infeasible. This dissertation presents methods of autonomously creating and refining optimal inverse functions for use as motion primitives. By clustering contiguous local optima, a continuous inverse function can be created by interpolating results. The additional clusters serve as alternatives if the chosen cluster is poorly suited to the situation. For multimodal problems, a population based optimization can efficiently search a large space. Staged learning offers a path to mimic the progression from novice to master, as seen in human learning. The dimension of the input wave parameterization, which is the number degrees of freedom for optimization, is incremented to allow for additional improvement. As the parameterization increases in order, the true optimal continuous-time control signal is approached. All previous experiences can be directly moved to the higher parameterization when expanding the parameterization, if a proper parameterization is selected. Incrementally increasing complexity and retaining experience efficiently optimizes to high dimensions when contrasted with undirected global optimizations, which would need to search the entire high dimension space. The method presented allows for unbounded resolution since the parameterization is not fixed at programming. This dissertation presents several methods that make steps towards the goal of learning and mastering motion-related tasks without programmed, task-specific heuristics. Trajectory optimization based on a high-level system description has been demonstrated for a robotic arm performing a pick-place task. In addition, the inverse optimal function was applied to optimizing robotic tracking precision in a method suitable for online tracking. Staging of the learning is able determine an optimal motor spin-up waveform despite large variations in system parameters. Global optimization, using a population based search, and unbounded resolution increasing provide the foundation for autonomously developing scalable motions superior to what can be designed by hand.
Advisors/Committee Members: Ordóñez, Raúl.
Subjects: Applied Mathematics; Artificial Intelligence; Electrical Engineering; Robotics; Robots
Keywords: Nonlinear Optimization; Optimal Control; Developmental Learning; Robotics; Inverse Functions; Locally Weighted Regression
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18.
Jiang, Hai.
The Effect of Amplitude Control and Randomness on Strongly Coupled Oscillator Arrays.
Degree: PhD, Electrical Engineering, 2009, University of Dayton
► Phased arrays have many applications such as Radar Communication, Satellite Communication, and…
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▼ Phased arrays have many applications such as Radar Communication, Satellite Communication, and Wireless Local Area Networks (WLAN). For the traditional phased array, a phase shifter is used with each antenna element to establish a constant phase progression along the antenna array. A constant phase progression will force the electromagnetic wave to add up so that the energy would radiate at a particular angle with respect to the array. However, it is difficult to integrate the bulky phase-shifters in the monolithic module, especially when the application involves a large number of elements. This dissertation studies an alternative phase beam-scanning technique using arrays of coupled oscillators (COA), which avoids the use of phase shifters. This technique of COA may reduce the complexity of phase control circuits and provide for a phased array of lower volume and weight. Consequently, it simplifies the architecture of the T/R module and reduces the overall cost. In this work, dynamic equations of the nonlinear COA with arbitrary coupling networks are derived using both time and frequency domain methods. From the dynamic analysis, it is shown that the phase distribution along the array, and hence the beam scanning angle of the array, can be controlled by free running frequencies of the coupled oscillators. The stability and nonlinear behaviors of synchronized coupled oscillators are studied via the nonlinear control theory and applied to radar beam scanning arrays. Analysis indicates that a stable, unique equilibrium point exists when choosing a specific set of free running frequencies, and it is associated with the desired phase shift but within a given range. By means of previous dynamic analysis, effects of amplitude dynamics are studied for COAs with uniform, triangular and Chebyshev amplitude distributions. The array with different coupling strengths, nonlinear parameters, and synchronization frequencies are considered. Results demonstrate that beam shapes and SLLs can be controlled for the coupled oscillator array using strong coupling. The influence of the random, free-running frequency distribution of the phase error in COAs, which causes the phase shift error and hence the error of main beam scanning angle (EMBSA), is also investigated through a Monte Carlo analysis. It is found that strongly COAs are more robust than weakly COAs under the same level of randomness in free running frequencies. Furthermore, when random deviations become larger, the robustness of strongly COA is especially obvious.
Advisors/Committee Members: Penno, Robert.
Subjects: Electrical engineering
Keywords: Coupled Oscillator Array; Phased Array; Amplitude Control; Dynamic Analysis; Stability Analysis; Transient Analysis; Robust Analysis; Effects of Amplitude Dynamics; Error of Main Beam Steering Angle; Strong Coupling; Monte Carlo Simulation.
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19.
Jin, Xiaodan.
Poisson Approximation to Image Sensor Noise.
Degree: MS, Electrical Engineering, 2010, University of Dayton
► POISSON APPROXIMATION OF IMAGE SENSOR NOISE Name: Jin, Xiaodan University of…
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▼ POISSON APPROXIMATION OF IMAGE SENSOR NOISE Name: Jin, Xiaodan University of Dayton Advisor: Dr. K. Hirakawa Noise is present in all images captured by image sensors. Due to photon emission and photoelectric effects that are the foundations of the ways in which quantum mechanics enable image sensors, in fact, random noise is a “necessary evil” of image sensors that will continue to require our attention. The goal of this research is to provide a comprehensive characterization of random noise in ways that enhance post-image-capture signal processing steps. We derive the Poisson approximation to model the measurement noise that is the result of photon arrival and photon recapture. A novel methodology to learn the parameters that describe the noise is developed. We conclude by presenting preliminary evidence that accurate noise modeling would improve image denoising, especially in the low photon count/high noise regimes.
Advisors/Committee Members: Hirakawa, Keigo.
Subjects: Electrical Engineering
Keywords: Image denoising, noise parameter estimation
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20.
John, Julian Daniel.
Acceleration of a Locally Tuned Sine Non Linear Video Enhancement Algorithm on GPGPU.
Degree: MS, Electrical Engineering, 2011, University of Dayton
► Computer Vision based applications support various domains such as medical, manufacturing, military…
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▼ Computer Vision based applications support various domains such as medical, manufacturing, military intelligence and surveillance systems. These applications can be divided into: image acquisition, pre-processing, feature extraction, detection or segmentation, and high-level processing. However these tasks are time intensive due to the compute bound nature of the algorithm. In this thesis, an algorithm, based on an image dependent nonlinear function, the Locally Tuned Sine Nonlinearity (LTSN), is accelerated using NVIDIA’s Computer Unified Device Architecture (CUDA) and the CPU. The main core of the algorithm is a nonlinear sine transfer function which is very flexible in enhancing the dark regions and compressing overexposed regions of an image. The video enhancement algorithm gave 21 frames per second compared to 9 frames per second for a 480p video. It is envisaged that the new technique would be useful for improving the visibility of scenes of night time driving and night security situations in real time.
Advisors/Committee Members: Taha, Tarek.
Subjects: Computer Engineering; Electrical Engineering; Engineering
Keywords: CUDA; GPU; GPGPU; Image Processing; Acceleration of Algorithm
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21.
Jones, Erica Nicole.
Development of Biopolymer Based Resonant Sensors.
Degree: MS, Electrical Engineering, 2010, University of Dayton
► Currently investigation of biopolymers for electronics, photonics and sensor applications is becoming…
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▼ Currently investigation of biopolymers for electronics, photonics and sensor applications is becoming more widespread. In this work, fabrication of a resonant sensor using various biopolymers has been accomplished. Biopolymers are becoming more and more common in the fabrication of electronic and photonic devices due to their inexpensiveness or cost effectiveness, eco-friendliness and ease of processing. The resonant sensor consists of an inductor in series with a variable capacitor composed of two electrodes separated by a chemically sensitive biopolymer. The resonant sensor is a multi-parameter device as one can measure the resonance frequency, amplitude and phase of the scattering parameters. Examples of chemical testing using the resonant sensor will be presented.
Advisors/Committee Members: Subramanyam, Guru.
Subjects: Biology; Engineering; Food science; Polymers; Technology
Keywords: Chemically Sensitive Biopolymer; Resonant Sensors; Variable Capacitor; Resonance Frequency; Scattering Parameters; Chemical Testing
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22.
Kordik, Andrew Michael.
Hardware Implementation of Post-Compression Rate-Distortion Optimization for EBCOT in JPEG2000.
Degree: MS, Electrical Engineering, 2011, University of Dayton
► As digital imaging sensors increase in size and capability, new ways to…
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▼ As digital imaging sensors increase in size and capability, new ways to efficiently store/transmit the data they generate must be examined. JPEG2000 is the latest image compression standard from the Joint Photographic Experts Group which improves over earlier standards in its ability to compress images while maintaining image quality. However, with the compression gain advantage over other image compression standard comes an additional computational cost. The JPEG2000 compressor is, substantially computationally complex than its predecessor, JPEG [12]. There are 2 basic procedures for irreversible rate reduction of JPEG2000 compressed imagery: quantization, and post-compression rate-distortion optimization (PCRD- Opt). Quantization is the method of reducing the dynamic range of transformed image data prior to coding. Quantization is a computationally simple method for data reduction, but lacks in control of the compressed file size and is sub-optimal in terms of image quality. PCRD-Opt, however, gives the user precise control of the output file size, and provides compressed imagery of the highest quality, per output bitrate [11]. This thesis is an embedded development of the PCRD-Opt algorithm, integrated into an FPGA-based JPEG2000 compression engine used for real-time compression of large-scale imagery. The embedded PCRD-Opt method provides imagery with a 2dB increase in quality over quantization on average, with a modest increase in complexity with an FPGA chip utilization increase of 11% in ALUTs and 15% increase in Memory ALUTs per Tier I encoder.
Advisors/Committee Members: Balster, Eric.
Subjects: Computer Engineering
Keywords: FPGA; JPEG2000; PCRD-opt; Optimal Truncation
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23.
Kundur, Abhinay.
Digital and Analog Signal Encryption and Decryption in Mid RF Range Using Hybrid Acousto-Optic Chaos.
Degree: MS, Electrical Engineering, 2012, University of Dayton
► Modern day communication techniques are often prone to hacking and disturbances in…
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▼ Modern day communication techniques are often prone to hacking and disturbances in the communication system while in transit from one place to another. Signal encryption using chaotic waves may be a good solution to this problem. A modulation scheme uses a carrier frequency to be modulated by the signal waveform, and generally the message can be readily decoded. A chaotic signal is a non-deterministic signal and not a well defined sinusoid. Hence, a modulated chaos wave is secure and cannot be decoded without knowledge of the chaos parameters. A chaotic signal is generated by carefully choosing the right set of parameters such as feedback gain, bias input and time delay. Encrypting a wave using a chaotic wave as a carrier also depends critically on these parameters. A signal used to encrypt a chaotic carrier can only be recovered or decoded by knowing exactly three parameter set, viz., the bias input alpha, feedback gain beta and time delay Td. Thus, the transmitter parameters serve as a decoding key, and hence signal encryption using a chaotic carrier provides data-security and reliability. In this research, we examine signal encryption using an acousto-optic chaos signal. For this, we generate a chaos signal with average frequency as high as 10MHz that is suitable for practical communication applications. We then examine encryption for different signals using the chaos wave with a set of fixed parameters. Finally, we recover the original signal using the same parameter set at the receiver and check for its robustness for cases where the receiver keys are mismatched or detuned. We derive the spectral characteristics using the simulation results from MATLAB by displaying waveforms on oscilloscopes, spectrum analyzers and so forth to check for the reliability or accuracy of the software results. We also perform a digital encryption using a gray scale image transmitted over the 10 MHz chaos as carrier and successfully decrypt the image at the receiver using low pass filter and then fine tuning the image. This research concludes with a rigorous check for the robustness of the system for both analog and digital data under single or multi parameter mismatch or detuning.
Advisors/Committee Members: Chatterjee, Monish R.
Subjects: Electrical Engineering; Optics
Keywords: Acousto-Optic; Image Encryption; Digital Encryption and Decryption; Hardware Reliability
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24.
Lucking, David Joseph.
FPGA Implementation of the JPEG2000 MQ Decoder.
Degree: MS, Electrical Engineering, 2010, University of Dayton
► As digital imaging techniques continue to advance, new image compression standards are…
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▼ As digital imaging techniques continue to advance, new image compression standards are needed to keep the transmission time and storage space low for increasing image sizes. The Joint Photographic Expert Group (JPEG) fulfilled this need with the ratification of the JPEG2000 standard in December of 2000. JPEG2000 adds many features to image compression technology but also increases the computational complexity of traditional decoders. To mitigate the added computational complexity, the committee developed the JPEG2000 algorithm to process parts in parallel, increasing the benefits of implementing the algorithm in application specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs). A flexible FPGA implementation of the MQ Decoder, the core component of the JPEG2000 decoding algorithm, is presented in this paper that successfully increases the throughput beyond previous designs.
Advisors/Committee Members: Balster, Eric J.
Subjects: Electrical engineering
Keywords: Image Processing; Image Compression; JPEG2000; EBCOT; MQ Decoder; FPGA; Reconfigurable; VHDL
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25.
Mannuru, Sravanthi.
A Fully Automated Geometric Lens Distortion Correction Method.
Degree: MS, Electrical Engineering, 2011, University of Dayton
► In applications such as computer vision and robotics, camera calibration is required…
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▼ In applications such as computer vision and robotics, camera calibration is required to correct geometric lens distortion of images. The problem with most techniques is that they require human involvement in the calibration process. This thesis proposes a new algorithm for camera calibration with no human involvement. Typically in camera calibration process, an image of a calibration target (usually a checkerboard) is acquired for distortion correction. The checkerboard is used because it has known features and is easily segmented. If the image of checkerboard pattern undergoes distortion when the image is captured, and the distortion may be determined by analyzing the image of the checkerboard. The proposed process for coefficient estimation is accomplished by segmenting out the checkerboard of a acquired image. The segmentation is done by finding the connected pixels (components), labeling the connected components and filtering out the unnecessary components from the acquired image. Then the algorithm uses sobel edge detection to detect the vertical and horizontal edges of the checkerboard, because the lines can be used to measure the displacement of image coordinates from their ideal location. Next, the proposed distortion-correction model is applied to the edges of the image with a set of correction coefficients, resulting a set of corrected images. Next the best fit line (synthesized line) is found for each observed line in the each corrected image, and the squared distance between each synthesized and observed line is calculated in each corrected image. The average squared distance is then calculated for each corrected image. Finally, the minimum average distance is found for a set of corrected images in order to obtain the respective image correction coefficients. Both synthetically generated images and natural images have been used to measure the performance of the proposed algorithm. The amount of distortion present in images before and after correction are represented graphically, and results show that the proposed, fully automated algorithm provides equivalent results when compared to other methods which require human involvement.
Advisors/Committee Members: Balster, Eric.
Subjects: Biomedical Research; Electrical Engineering
Keywords: Radial Distortion; Radial Distortion Correction; Calibration Process; Camera Calibration
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26.
McGuinness, Christopher.
A Signal Quality-Based Study of Two Compensation Methods for Nonlinear Flash ADCs.
Degree: MS, Electrical Engineering, 2011, University of Dayton
► The analog-to-digital conversion of signals is a necessity in a world with…
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▼ The analog-to-digital conversion of signals is a necessity in a world with an increasing dependance on digital systems. During the process of digitizing signals, signal spectra are nonlinearly distorted due to the nonideal conversion device. Many kinds of nonlinear distortion can occur: inconsistent quantization intervals, clocking inconsistencies, and biasing errors are among the most prevalent. Of these sources, inconsistent quantization intervals is the most degrading to signal fidelity. Significant reduction in spurious free dynamic range, total harmonic distortion, and effective number of bits can be caused by small amounts of quantization error. Thus, methods for compensating the effects of nonlinear quantization have been a topic of considerable research in data conversion circles. Two promising methods in particular, dynamic element matching (DEM) and bit extended error tables (BEET), are simulated and compared to various converter families. It is shown that BEET compensation provides larger improvements for a larger number of converters than if DEM is used.
Advisors/Committee Members: Balster, Eric.
Subjects: Electrical Engineering
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27.
McNichols, John M.
Design and Implementation of an Embedded NIOS II System for JPEG2000 Tier II Encoding.
Degree: MS, Electrical Engineering, 2012, University of Dayton
► Image compression standards continually strive to to achieve higher compression ratios while…
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▼ Image compression standards continually strive to to achieve higher compression ratios while maintaining image quality. In addition to these goals, new applications require expanded features and flexibility as compared to existing compression standards. JPEG2000 is the latest in the line of image compression standards, offering higher compression ratios than its predecessor JPEG while maintaining comparable image quality. In addition, JPEG2000 offers an extended range of features including bit-rate control, region of interest coding and file-stream scalability with respect to resolution, image quality, components and spatial region. However, these additional features come with associated costs, primarily in the form of computational complexity. Due to the increased computational costs, JPEG2000 has not achieved the same wide-spread usage as JPEG. However, there are a number of specialized applications such as medical imaging and wide-area surveillance which demand the extended features offered by JPEG2000. These applications generally deal with high resolution imagery, resulting in extremely long encoding times when using consumer off the shelf platforms. As a result, many hardware implementations of the most computationally complex portions of JPEG2000, namely Tier I encoding, have been proposed. This thesis proposes using an embedded soft-core processor on a Field Programmable Gate Array (FPGA) for JPEG2000 code stream organization, known as Tier II. The soft-core processor chosen, Altera's NIOS II core, is coupled with existing Discrete Wavelet Transform (DWT) and Tier I implementations on a single FPGA to realize a fully embedded JPEG2000 encoder. Results show the feasibility of using an embedded soft-core processor on a FPGA to perform Tier II processing for JPEG2000.
Advisors/Committee Members: Balster, Eric.
Subjects: Computer Engineering; Electrical Engineering
Keywords: JPEG2000; NIOS II; Embedded processing; Embedded systems; System-on-chip; FPGA; Image processing; Image compression
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28.
Pan, Kuan-Chang.
Ferroelectric Barium Strontium Titanate Thin-Film Varactor Based Reconfigurable Antenna.
Degree: MS, Electrical Engineering, 2011, University of Dayton
► The main objective of this research is to develop an antenna that…
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▼ The main objective of this research is to develop an antenna that can shift its frequency of operation over a band of frequencies. A novel printed antenna for frequency reconfigurable applications is presented. A coplanar waveguide (CPW) antenna was designed on a non-grounded substrate, with the center conductor of the CPW transmission line connected to a bowtie patch. The bowtie structure is the radiating element and lies in the inner space of the annulus created by the CPW ground lines. The antenna has a compact structure with the total area 6×6 mm2. The frequency of this antenna can be reconfigured from 5.75 GHz to 6.19 GHz by tuning a varactor loaded with the antenna. Applying a DC bias voltage to the ferroelectric (FE) Barium Strontium Titanate (BST) varactor alters the S-parameters of the antenna. The return loss of the antenna in the frequency of operation is below -10 dB, which fits the requirement of a working antenna. The frequency of operation shifts from a lower frequency to a higher frequency by increasing the DC bias voltage. This reconfigurable antenna was designed, simulated, and fabricated, and the test and measurement results are shown.
Advisors/Committee Members: Subramanyam, Guru.
Subjects: Electrical Engineering; Electromagnetics
Keywords: ferroelectric; BST; thin-film; varactor; reconfigurable antenna; miniaturized; CPW; bowtie; patch
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29.
Patterson, Mark Alan.
A Passive Wireless Platform for Chemical-Biological Sensors.
Degree: PhD, Electrical Engineering, 2012, University of Dayton
► This research presents several different platforms for detecting chemical or biological agents…
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▼ This research presents several different platforms for detecting chemical or biological agents without the use of probes or wires and without the use of a battery. These platforms all use an interrogator to transmit power through either radio or low frequency electromagnetic waves to a sensor device. The sensor device has a functionalized surface which aids in selectivity to the analyte of interest. The sensor device sends back a portion of the power through radio frequency waves with altered frequency, amplitude and phase. The characteristics of the received signal contain the information about the analyte of interest. The platforms were tested with several volatile organic compounds, gasoline, sulfuric acid, hydraulic fluid, and chlorine. The results were statistically significant.
Advisors/Committee Members: Subramanyam, Guru.
Subjects: Biomedical Engineering; Electrical Engineering; Electromagnetics
Keywords: chemical sensor; wireless power transfer
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30.
Ross, Lewis Tyson.
Automated Growing Rod for the Treatment of Juvenile Scoliosis.
Degree: PhD, Electrical Engineering, 2012, University of Dayton
► Severe scoliosis, when detected in a juvenile, can be treated and upon…
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▼ Severe scoliosis, when detected in a juvenile, can be treated and upon conclusion of the treatment, will result in a spine with little or no curvature. However, this treatment requires the child to undergo surgery where a device known as a growing rod is implanted on the spine of the juvenile. After the initial surgery the child then returns every six months to have the rods "lengthened" approximately one centimeter to keep up with the child's growth. The purpose of this project is to develop an automated growing rod system using an on-board microprocessor for treatment feedback control. The ultimate goal of the design of the automated growing rod is to limit or remove the requirement of a patient to undergo surgery for rod adjustments by the physician. Utilizing new control technology and hardware design, juvenile scoliosis can be treated in a non-invasive fashion with the efficacy that the current growing rod treatment provides, while reducing cost and improving treatment control. This study has designed and built a test automated growing rod system, demonstrated system functionality, and shown that the system is realizable in an ex-situ lab environment.
Advisors/Committee Members: Weber, John G.
Subjects: Biomedical Engineering; Biomedical Research; Engineering
Keywords: Growing rod; Juvenile scoliosis; Bone lengthening; Implant
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