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Articles 1 - 30 of 47
Full-Text Articles in Electrical and Computer Engineering
Detection Of Unauthorized Transmissions In A Frequency Spectrum Using A Wireless Sensor Network, Benjamin Roehrig, Joel Brinkman, Dylan Zupec, Jannette Gonzalez
Detection Of Unauthorized Transmissions In A Frequency Spectrum Using A Wireless Sensor Network, Benjamin Roehrig, Joel Brinkman, Dylan Zupec, Jannette Gonzalez
Honors Capstones
A prototype for a wireless sensor network has been designed to detect and identify unauthorized wireless transmissions in a frequency spectrum. This prototype design is intended to detect unauthorized transmissions within the FM band of frequencies independently at individual nodes with Software Defined Radio receivers and transmit that information to a fusion center for aggregation using a Bluetooth Low Energy mesh network. Aggregated results will be displayed to the user through a Graphical User Interface at the fusion center.
Automotive Collision Warning System Retrofit, Ethan Clark Najmy
Automotive Collision Warning System Retrofit, Ethan Clark Najmy
Electrical Engineering
In the early 2000s, few automakers began implementing forward collision warning systems in their cars. As technology advanced this system became available on more and more luxury cars. In recent years, this technology has spread to more affordable vehicles driven every day. However, as this technology has only recently advanced to less expensive, more economical cars, older vehicles of the same model may not have this advanced and important safety feature. This project investigates and creates a preliminary design for an affordable, easy-to-install, forward collision warning system that can be retrofitted to vehicles without the system currently installed. Using a …
Emotion Detection Using An Ensemble Model Trained With Physiological Signals And Inferred Arousal-Valence States, Matthew Nathanael Gray
Emotion Detection Using An Ensemble Model Trained With Physiological Signals And Inferred Arousal-Valence States, Matthew Nathanael Gray
Electrical & Computer Engineering Theses & Dissertations
Affective computing is an exciting and transformative field that is gaining in popularity among psychologists, statisticians, and computer scientists. The ability of a machine to infer human emotion and mood, i.e. affective states, has the potential to greatly improve human-machine interaction in our increasingly digital world. In this work, an ensemble model methodology for detecting human emotions across multiple subjects is outlined. The Continuously Annotated Signals of Emotion (CASE) dataset, which is a dataset of physiological signals labeled with discrete emotions from video stimuli as well as subject-reported continuous emotions, arousal and valence, from the circumplex model, is used for …
Electromechanical Fatigue Properties Of Dielectric Elastomer Stretch Sensors Under Orthopaedic Loading Conditions, Andrea Karen Persons
Electromechanical Fatigue Properties Of Dielectric Elastomer Stretch Sensors Under Orthopaedic Loading Conditions, Andrea Karen Persons
Theses and Dissertations
Fatigue testing of stretch sensors often focuses on high amplitude, low-cycle fatigue (LCF) behavior; however, when used for orthopaedic, athletic, or ergonomic assessments, stretch sensors are subjected to low amplitude, high-cycle fatigue (HCF) conditions. As an added layer of complexity, the fatigue testing of stretch sensors is not only focused on the life of the material comprising the sensor, but also on the reliability of the signal produced during the extension and relaxation of the sensor. Research into the development of a smart sock that can be used to measure the range of motion (ROM) of the ankle joint during …
Machine Learning Classification Of Digitally Modulated Signals, James A. Latshaw
Machine Learning Classification Of Digitally Modulated Signals, James A. Latshaw
Electrical & Computer Engineering Theses & Dissertations
Automatic classification of digitally modulated signals is a challenging problem that has traditionally been approached using signal processing tools such as log-likelihood algorithms for signal classification or cyclostationary signal analysis. These approaches are computationally intensive and cumbersome in general, and in recent years alternative approaches that use machine learning have been presented in the literature for automatic classification of digitally modulated signals. This thesis studies deep learning approaches for classifying digitally modulated signals that use deep artificial neural networks in conjunction with the canonical representation of digitally modulated signals in terms of in-phase and quadrature components. Specifically, capsule networks are …
New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams
New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams
Theses and Dissertations
A commonality in the many applications and domains where signal processing (SP)is applied is the detection of events. Detection in SP requires the identification of the occurrence of an event, within a signal, and distinguishing the occurrence from no event. In a classical application of SP, seismologists seek to detect abnormalities in an electromagnetic (EM) signal to detect or not detect the occurrence of an earthquake, represented as an anomalous EM pulse. Since many signals are noisy, such as those produced by a seismograph, it can be challenging to distinguish a significant EM pulse from incident noise. In SP, smoothing …
Error Prevention In Sensors And Sensor Systems, Pedro J. Chacon Dominguez
Error Prevention In Sensors And Sensor Systems, Pedro J. Chacon Dominguez
LSU Doctoral Dissertations
Achievements in all fields of engineering and fabrication methods have led towards optimization and integration of multiple sensing devices into a concise system. These advances have caused significant innovation in various commercial, industrial, and research efforts. Integrations of subsystems have important applications for sensor systems in particular. The need for reporting and real time awareness of a device’s condition and surroundings have led to sensor systems being implemented in a wide variety of fields. From environmental sensors for agriculture, to object characterization and biomedical sensing, the application for sensor systems has impacted all modern facets of innovation. With these innovations, …
Chaos-Based Coffee Can Radar System, Conor Willsie, Rong Chen
Chaos-Based Coffee Can Radar System, Conor Willsie, Rong Chen
Honors Theses
Linear frequency modulated (LFM) radar systems are simple and easy to implement, making them ideal for inexpensive undergraduate research projects. Unfortunately, LFM radar schemes have multiple limitations that make them unviable in many real-world applications. Given the limitations of LFM radar systems, we propose a chaos-based frequency modulated (CBFM) system. In this paper, we present the theory, design, and experimental verification of a CBFM radar system that has both ranging and synthetic aperture radar imaging capabilities. The performance of our CBFM system is compared to that of the LFM system designed by MIT. We document many challenges and unforeseen obstacles …
Deep Learning Assisted Intelligent Visual And Vehicle Tracking Systems, Liang Xu
Deep Learning Assisted Intelligent Visual And Vehicle Tracking Systems, Liang Xu
Theses and Dissertations
Sensor fusion and tracking is the ability to bring together measurements from multiple sensors of the current and past time to estimate the current state of a system. The resulting state estimate is more accurate compared with the direct sensor measurement because it balances between the state prediction based on the assumed motion model and the noisy sensor measurement. Systems can then use the information provided by the sensor fusion and tracking process to support more-intelligent actions and achieve autonomy in a system like an autonomous vehicle. In the past, widely used sensor data are structured, which can be directly …
Atmospheric Turbulence Distortion In Video: Restoration Utilizing Sparse Analysis, Benjamin J. Sanda
Atmospheric Turbulence Distortion In Video: Restoration Utilizing Sparse Analysis, Benjamin J. Sanda
Dissertations
The removal of atmospheric turbulence (AT) distortion in long range imaging is one of the most challenging areas of research in imaging processing with an immediate need for solutions in several applications such as in military and transportation systems. AT exacerbates distortion due to non-linear geometric blur and scintillations in long-distance images and videos, severely reducing image quality and information interpretation. AT negatively impacts both human and computer vision systems, compromising visibility essential for accurate object identification and tracking.
In this dissertation, a novel sparse analysis framework is developed to address efficient AT blur and scintillation removal in video. Operating …
An Adaptive Approach To Gibbs’ Phenomenon, Jannatul Ferdous Chhoa
An Adaptive Approach To Gibbs’ Phenomenon, Jannatul Ferdous Chhoa
Master's Theses
Gibbs’ Phenomenon, an unusual behavior of functions with sharp jumps, is encountered while applying the Fourier Transform on them. The resulting reconstructions have high frequency oscillations near the jumps making the reconstructions far from being accurate. To get rid of the unwanted oscillations, we used the Lanczos sigma factor to adjust the Fourier series and we came across three cases. Out of the three, two of them failed to give us the right reconstructions because either it was removing the oscillations partially but not entirely or it was completely removing them but smoothing out the jumps a little too much. …
Schrödinger Filtering: A Novel Technique For Removing Gradient Artifact From Electroencephalography Data Acquired During Functional Magnetic Resonance Imaging, Gabriel Bruno Benigno
Schrödinger Filtering: A Novel Technique For Removing Gradient Artifact From Electroencephalography Data Acquired During Functional Magnetic Resonance Imaging, Gabriel Bruno Benigno
Electronic Thesis and Dissertation Repository
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are complementary modalities commonly acquired simultaneously to study brain function with high spatial and temporal resolution. The time-varying gradient fields from fMRI induce massive-amplitude artifacts (GRAs) that overlap in time and frequency with EEG, making GRA removal a challenge for which no satisfactory solution yet exists. We present a new GRA removal method termed Schrödinger filtering (SF). SF is based on semi-classical signal analysis in which a signal is decomposed into a series of energy-based components using the discrete spectrum of the Schrödinger operator. Using a publicly available dataset, we compared our …
A Model-Based Framework For The Smart Manufacturing Of Polymers, Santiago D. Salas Ortiz
A Model-Based Framework For The Smart Manufacturing Of Polymers, Santiago D. Salas Ortiz
LSU Doctoral Dissertations
It is hard to point a daily activity in which polymeric materials or plastics are not involved. The synthesis of polymers occurs by reacting small molecules together to form, under certain conditions, long molecules. In polymer synthesis, it is mandatory to assure uniformity between batches, high-quality of end-products, efficiency, minimum environmental impact, and safety. It remains as a major challenge the establishment of operational conditions capable of achieving all objectives together. In this dissertation, different model-centric strategies are combined, assessed, and tested for two polymerization systems.
The first system is the synthesis of polyacrylamide in aqueous solution using potassium persulfate …
Dark Current Rts-Noise In Silicon Image Sensors, Benjamin William Hendrickson
Dark Current Rts-Noise In Silicon Image Sensors, Benjamin William Hendrickson
Dissertations and Theses
Random Telegraph Signal (RTS) noise is a random noise source defined by discrete and metastable changes in the magnitude of a signal. Though observed in a variety of physical processes, RTS is of particular interest to image sensor fabrication where progress in the suppression of other noise sources has elevated its noise contribution to the point of approaching the limiting noise source in scientific applications.
There have been two basic physical sources of RTS noise reported in image sensors. The first involves a charge trap in the oxide layer of the source follower in a CMOS image sensor. The capture …
2018 Ieee Signal Processing Cup: Forensic Camera Model Identification Challenge, Michael Geiger
2018 Ieee Signal Processing Cup: Forensic Camera Model Identification Challenge, Michael Geiger
Honors Theses
The goal of this Senior Capstone Project was to lead Union College’s first ever Signal Processing Cup Team to compete in IEEE’s 2018 Signal Processing Cup Competition. This year’s competition was a forensic camera model identification challenge and was divided into two separate stages of competition: Open Competition and Final Competition. Participation in the Open Competition was open to any teams of undergraduate students, but the Final Competition was only open to the three finalists from Open Competition and is scheduled to be held at ICASSP 2018 in Calgary, Alberta, Canada. Teams that make it to the Final Competition will …
Detecting Suicide Risk From Wristworn Activity Tracker Data Using Machine Learning Approaches, Pallavi Atluri
Detecting Suicide Risk From Wristworn Activity Tracker Data Using Machine Learning Approaches, Pallavi Atluri
Electrical Engineering Theses
Suicide is a prevalent cause of death worldwide and depression is a primary concern of many suicidal acts. It is possible that an individual during depression never has any suicidal thoughts at all. On the other hand, some individuals in stable condition with no apparent symptoms of depression feel urges to commit suicide (suicidal ideation). Many such individuals never let anyone know what they are feeling or planning. Suicidal ideation considered an important precursor to suicidal acts.
Detecting the suicide risk in individuals with mood disorders is a major challenge. The current clinical practice to assess suicide risk in these …
Real-Time Audio-Midi Controller, Brian Shino Balberchak
Real-Time Audio-Midi Controller, Brian Shino Balberchak
Computer Engineering
Most MIDI controllers used in music production use a regular keyboard to generate the MIDI notes that are sent to the synthesizer. This project aims to provide the user with a different way of generating MIDI data: by playing an instrument of their choice with a passive electronic pickup to generate MIDI notes that correspond with the fundamental frequency of the musical pitch being played. The pitch-detecting algorithm used in this application utilizes a modified form of auto-correlation.
As an embedded systems project that uses signal-processing techniques, the knowledge of topics from the following courses was essential:
EE 211: Op-Amp …
Feasibility Of Melville Marginalia Authorship Differentiation, Aaron Burdin
Feasibility Of Melville Marginalia Authorship Differentiation, Aaron Burdin
Boise State University Theses and Dissertations
We examine the feasibility of using image processing techniques to determine differentiation in authorship of historical pencil marks. Pencil marks with unattributed and attributed authorship are segmented from digital images of historical books. Analysis is performed on five features that are extracted from the "vertical" pencil marks, with those features used as a basis for authorship of marks. These marks consist of single stroke marks that are interspersed in the same document. We describe the challenges of the digital format that we were given and the steps taken in using autonomous segmentation to save pixel locations of marks. Five mark …
Low-Resolution Adc Receiver Design, Mimo Interference Cancellation Prototyping, And Phy Secrecy Analysis., Chen Cao
Electronic Theses and Dissertations
This dissertation studies three independent research topics in the general field of wireless communications. The first topic focuses on new receiver design with low-resolution analog-to-digital converters (ADC). In future massive multiple-input-multiple-output (MIMO) systems, multiple high-speed high-resolution ADCs will become a bottleneck for practical applications because of the hardware complexity and power consumption. One solution to this problem is to adopt low-cost low-precision ADCs instead. In Chapter II, MU-MIMO-OFDM systems only equipped with low-precision ADCs are considered. A new turbo receiver structure is proposed to improve the overall system performance. Meanwhile, ultra-low-cost communication devices can enable massive deployment of disposable wireless …
Applications In Low-Power Phased Array Weather Radars, Robert A. Palumbo Jr
Applications In Low-Power Phased Array Weather Radars, Robert A. Palumbo Jr
Doctoral Dissertations
Low-cost X-band radars are an emerging technology that offer significant advantages over traditional systems for weather remote sensing applications. X-band radars provide enhanced angular resolution at a fraction of the aperture size compared to larger, lower frequency systems. Because of their low cost and small form factor, these radars can now be integrated into more research and commercial applications. This work presents research and development activities using a low-cost, X-band (9410 MHz) Phase-Tilt Radar. The phase-tilt design is a novel phased array architecture that allows for rapid electronic scanning in azimuth and mechanical tilting in elevation, as a compromise between …
Enhanced Sonar Array Target Localization Using Time-Frequency Interference Phenomena, Jordan Almon Shibley
Enhanced Sonar Array Target Localization Using Time-Frequency Interference Phenomena, Jordan Almon Shibley
Dissertations and Theses
The ability of traditional active sonar processing methods to detect targets is often limited by clutter and reverberation from ocean environments. Similarly, multipath arrivals from radiating sources such as ships and submarines are received at sensors in passive sonar systems. Reverberation and multipath signals introduce constructive and destructive interference patterns in received spectrograms in both active and passive sonar applications that vary with target range and frequency. The characterization and use of interference phenomena can provide insights into environmental parameters and target movement in conjunction with standard processing methods including spectrograms and array beamforming.
This thesis focuses on utilizing the …
Piezoelectric Transformer And Hall-Effect Based Sensing And Disturbance Monitoring Methodology For High-Voltage Power Supply Lines, Sneha Arun Lele
Piezoelectric Transformer And Hall-Effect Based Sensing And Disturbance Monitoring Methodology For High-Voltage Power Supply Lines, Sneha Arun Lele
Electronic Thesis and Dissertation Repository
Advancements in relaying algorithms have led to an accurate and robust protection system widely used in power distribution. However, in low power sections of relaying systems, standard voltage and current measurement techniques are still used. These techniques have disadvantages like higher cost, size, electromagnetic interference, resistive losses and measurement errors and hence provide a number of opportunities for improvement and integration. We present a novel microsystem methodology to sense low-power voltage and current signals and detect disturbances in high-voltage power distribution lines. The system employs dual sensor architecture that consists of a piezoelectric transformer in combination with Hall-effect sensor, used …
An Inquiry: Effectiveness Of The Complex Empirical Mode Decomposition Method, The Hilbert-Huang Transform, And The Fast-Fourier Transform For Analysis Of Dynamic Objects, Kristen L. Wallis
An Inquiry: Effectiveness Of The Complex Empirical Mode Decomposition Method, The Hilbert-Huang Transform, And The Fast-Fourier Transform For Analysis Of Dynamic Objects, Kristen L. Wallis
Theses and Dissertations
A review of current signal analysis tools show that new techniques are required for an enhanced fidelity or data integrity. Recently, the Hilbert-Huang transform (HHT) and its inherent property, the Empirical Mode Decomposition (EMD) technique, have been formerly investigated. The technique of Complex EMD (CEMD) was also explored. The scope of this work was to assess the CEMD technique as an innovative analysis tool. Subsequent to this, comparisons between applications of the Hilbert transform (HT) and the Fast-Fourier transform (FFT) were analyzed. MATLAB was implemented to model signal decomposition and the execution of mathematical transforms for generating results. The CEMD …
Application Of Signal Advance Technology To Electrophysiology, Chris M. Hymel
Application Of Signal Advance Technology To Electrophysiology, Chris M. Hymel
Dissertations & Theses (Open Access)
Medical instrumentation used in diagnosis and treatment relies on the accurate detection and processing of various physiological events and signals. While signal detection technology has improved greatly in recent years, there remain inherent delays in signal detection/ processing. These delays may have significant negative clinical consequences during various pathophysiological events. Reducing or eliminating such delays would increase the ability to provide successful early intervention in certain disorders thereby increasing the efficacy of treatment.
In recent years, a physical phenomenon referred to as Negative Group Delay (NGD), demonstrated in simple electronic circuits, has been shown to temporally advance the detection of …
Fusion Of Inertial Sensors And Orthogonal Frequency Division Multiplexed (Ofdm) Signals Of Opportunity For Unassisted Navigation, Jason G. Crosby
Fusion Of Inertial Sensors And Orthogonal Frequency Division Multiplexed (Ofdm) Signals Of Opportunity For Unassisted Navigation, Jason G. Crosby
Theses and Dissertations
The advent of the global positioning system (GPS) has provided worldwide high-accuracy position measurements. However, GPS may be rendered unavailable by jamming, disruption of satellites, or simply by signal shadowing in urban environments. Thus, this thesis considers fusion of Inertial Navigation Systems (INS) and Orthogonal Frequency Division Multiplexed (OFDM) signals of opportunity (SOOP) for navigation. Typical signal of opportunity navigation involves the use of a reference receiver and uses time difference of arrival (TDOA) measurements. However, by exploiting the block structure of OFDM communication signals, the need for the reference receiver is reduced or possibly removed entirely. This research uses …
Joint Image And Pupil Plane Reconstruction Algorithm Based On Bayesian Techniques, James D. Phillips
Joint Image And Pupil Plane Reconstruction Algorithm Based On Bayesian Techniques, James D. Phillips
Theses and Dissertations
The focus of this research was to develop an joint pupil and focal plane image recovery algorithm for use with coherent LADAR systems. The benefits of such a system would include increased resolution with little or no increase in system weight and volume as well as allowing for operation in the absence of natural light since the target of interest would be actively illuminated. Since a pupil plane collection aperture can be conformal, such a system would also potentially allow for the formation of large synthetic apertures. The system is demonstrated to be robust and in all but extreme cases …
Laser Covariance Vibrometry For Unsymmetrical Mode Detection, Michael C. Kobold
Laser Covariance Vibrometry For Unsymmetrical Mode Detection, Michael C. Kobold
Theses and Dissertations
Simulated cross - spectral covariance (CSC) from optical return from simulated surface vibration indicates CW phase modulation may be an appropriate phenomenology for adequate classification of vehicles by structural mode. The nonlinear structural to optical relationship is close to unity, avoiding nulls and high values; optical return contains sufficient spectral ID information necessary for data clustering. The FE model has contact between the homogeneous rolled armor and vehicle hull, a simple multi - layer skin model typical of most vehicles. Most of the high frequency energy moved to lower frequencies. This nonlinearity segments contact vibration modes into two classes: symmetrical …
Blind Deconvolution Of Anisoplanatic Images Collected By A Partially Coherent Imaging System, Adam Macdonald
Blind Deconvolution Of Anisoplanatic Images Collected By A Partially Coherent Imaging System, Adam Macdonald
Theses and Dissertations
Coherent imaging systems offer unique benefits to system operators in terms of resolving power, range gating, selective illumination and utility for applications where passively illuminated targets have limited emissivity or reflectivity. This research proposes a novel blind deconvolution algorithm that is based on a maximum a posteriori Bayesian estimator constructed upon a physically based statistical model for the intensity of the partially coherent light at the imaging detector. The estimator is initially constructed using a shift-invariant system model, and is later extended to the case of a shift-variant optical system by the addition of a transfer function term that quantifies …
Characterization And Design Of High-Level Vhdl I/Q Frequency Downconverter Via Special Sampling Scheme, Jesse P. Somann
Characterization And Design Of High-Level Vhdl I/Q Frequency Downconverter Via Special Sampling Scheme, Jesse P. Somann
Theses and Dissertations
This study explores the characterization and implementation of a Special Sampling Scheme (SSS) for In-Phase and Quad-Phase (I/Q) down conversion utilizing top-level, portable design strategies. The SSS is an under-developed signal sampling methodology that can be used with military and industry receiver systems, specifically, United States Air Force (USAF) video receiver systems. The SSS processes a digital input signal-stream sampled at a specified sampling frequency, and down converts it into In-Phase (I) and Quad-Phase (Q) output signal-streams. Using the theory and application of the SSS, there are three main objectives that will be accomplished: characterization of the effects of input, …
Passive Ranging Using Atmospheric Oxygen Absorption Spectra, Michael R. Hawks
Passive Ranging Using Atmospheric Oxygen Absorption Spectra, Michael R. Hawks
Theses and Dissertations
The depth of absorption bands in observed spectra of distant, bright sources can be used to estimate range to the source. A novel approach is presented and demonstrated using observations of the oxygen absorption band near 762 nm. Range is estimated by comparing observed values of band-average absorption against curves derived from either historical data or model predictions. Curves are based on fitting a random band model to the data, which reduces average range error by 67% compared to the Beer's Law model used in previous work. A new modification to existing band models for long, inhomogeneous paths is presented …