Engineering Commons^™

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.

Development Of The Digital Signal Processing For The Space Weather Probes Version 2 Sensor Using The Matlab/Simulink Environment, Benjamin J. Lewis

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Space Weather Probes (SWP) is an instrument that provides measurements of the plasma environment of the ionosphere. SWP was flown on the Scintillation Prediction Observation Task (SPORT) mission, a joint mission between the United States of America and Brazil. This thesis will develop the digital signal processing (DSP) hardware design for the Space Weather Probes version 2 (SWP2). The data from these instruments will be used to determine the density and temperature of the local plasma, as well as the electric field in the local plasma. This thesis presents the design and testing of the DSP designs for all of …

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

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

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

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 …

Real Time Simulation And Hardware In The Loop Methods For Power Electronics Power Distribution Systems, Michele Difronzo

Theses and Dissertations

System level testing of Power Electronics Power Distribution Systems (PEPDS) can be challenging when fine temporal resolution is required (time step below 100-200ns). In the recent years, our research group has proposed various methods to simulate in real-time PEPDS using FPGAs and time step as small as 50ns. While the proposed methods allow achieving the desired temporal resolution, they are extremely demanding in terms of resources usage and the size of the PEPDS that can be simulated on a single FPGA is strongly limited.

In this dissertation -work that takes as an example application the US Navy electric Ship Zonal …

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

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

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

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 …

Clustered Hyperspectral Target Detection, Sean Onufer Stalley

Dissertations and Theses

Aerial target detection is often used to search for relatively small things over large areas of land. Depending on the size and signature of the target, detection can be a very easy or very difficult task. By capturing images with several hundred color channels, hyperspectral sensors provide a new way of looking at this task, both literally and figuratively. Hyperspectral sensors can be used in many aerial target detection tasks such as identifying unhealthy trees in a forest, searching for minerals at a mining site, or finding the sources of chemical leaks at a factory. The high spectral resolution of …

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

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

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 …

Physics-Based Signal Processing Methods For Terahertz Non-Destructive Evaluation Of Layered Media, Scott G. Schecklman

Dissertations and Theses

In recent years Terahertz (THz) time domain spectroscopy has emerged as a promising new technology with potential applications in a variety of fields, including industrial manufacturing, security screening and medical imaging. Pulsed THz systems are uniquely suited for non-destructive evaluation (NDE) of the sub-surface layers of dielectric packaging and coating materials, because they provide high dynamic range over a wide bandwidth in the far infrared portion of the electromagnetic spectrum. Often the dielectric materials of the packaging and/or surface coating layers exhibit relatively low loss and abrupt changes in the refractive index at the layer boundaries can be observed as …

Uhf And Microwave Phase-Modulated Scattering Array, Nasr Nomas Hussein Alkhafaji

Dissertations and Theses

This dissertation investigates the use an array of active nonlinear elements, with particular emphasis on controlling distortion products generated by nonlinear elements in space rather than using conventional ways such as transmission lines, waveguides, and power dividers and combiners. The nonlinear elements are made of assemblies of antennas and electronic switches, called modulated scatterers (MSs). These so-called MSs elements are utilized in a wide variety of applications such as radio frequency identification (RFID) systems, microwave imaging, Internet-of-Things sensors, etc. However, no research work has been reported in the literature regarding exploiting and controlling several distortion products generated by MSs at …

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

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

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

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

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 …

Temperature Robust Longwave Infrared Hyperspectral Change Detection, Nicholas A. Durkee

Browse all Theses and Dissertations

In this thesis, we develop and evaluate change detection algorithms for longwave infrared (LWIR) hyperspectral imagery. Because measured radiance in the LWIR domain depends on unknown surface temperature, care must be taken to prevent false alarms resulting from in-scene temperature differences that appear as material changes. We consider fewer variables. Examples using synthetic and measured data quantify the computational complexity of the proposed methods and demonstrate orders of magnitude reduction in false alarm rates relative to existing methods. Four strategies to mitigate this effect. In the first, pre-processing via traditional temperatureemissivity separation yields approximately temperature-invariant emissivity vectors for use in …

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 …

Investigating Key Techniques To Leverage The Functionality Of Ground/Wall Penetrating Radar, Yu Zhang

Graduate College Dissertations and Theses

Ground penetrating radar (GPR) has been extensively utilized as a highly efficient and non-destructive testing method for infrastructure evaluation, such as highway rebar detection, bridge decks inspection, asphalt pavement monitoring, underground pipe leakage detection, railroad ballast assessment, etc. The focus of this dissertation is to investigate the key techniques to tackle with GPR signal processing from three perspectives: (1) Removing or suppressing the radar clutter signal; (2) Detecting the underground target or the region of interest (RoI) in the GPR image; (3) Imaging the underground target to eliminate or alleviate the feature distortion and reconstructing the shape of the target …

Asynchronous Data Processing Platforms For Energy Efficiency, Performance, And Scalability, Liang Men

Graduate Theses and Dissertations

The global technology revolution is changing the integrated circuit industry from the one driven by performance to the one driven by energy, scalability and more-balanced design goals. Without clock-related issues, asynchronous circuits enable further design tradeoffs and in operation adaptive adjustments for energy efficiency. This dissertation work presents the design methodology of the asynchronous circuit using NULL Convention Logic (NCL) and multi-threshold CMOS techniques for energy efficiency and throughput optimization in digital signal processing circuits. Parallel homogeneous and heterogeneous platforms implementing adaptive dynamic voltage scaling (DVS) based on the observation of system fullness and workload prediction are developed for balanced …

Evaluating Features For Broad Species Based Classification Of Bird Observations Using Dual-Polarized Doppler Weather Radar, Sheila Werth

Masters Theses

Wind energy is one of the fastest-growing segments of the world energy market; however, wind energy facilities can have detrimental effects on wildlife, especially birds and bats. The ability to monitor vulnerable species in the vicinity of proposed wind sites could enable site selection that favors more vulnerable species, but current monitoring tools lack this classification capability. This work analyzes polarimetric and Doppler measurements of migrating birds for species based variation.

A novel two stage feature extraction technique was developed to enable comparison between birds. Stage one involves mapping time changing radar measurements to the birds behavioral state in time …

Experimental And Computational Studies Of Cortical Neural Network Properties Through Signal Processing, Wesley Patrick Clawson

Graduate Theses and Dissertations

Previous studies, both theoretical and experimental, of network level dynamics in the cerebral cortex show evidence for a statistical phenomenon called criticality; a phenomenon originally studied in the context of phase transitions in physical systems and that is associated with favorable information processing in the context of the brain. The focus of this thesis is to expand upon past results with new experimentation and modeling to show a relationship between criticality and the ability to detect and discriminate sensory input. A line of theoretical work predicts maximal sensory discrimination as a functional benefit of criticality, which can then be characterized …

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 …