Signal Processing Commons^™

Examining Physiological Responses To Misophonic Triggers, Christian O'Reilly, Xuan Yang, Sewon Oh, Doug Wedell, Svetlana Shinkareva

Faculty Publications

We collected and analyzed an array of biosignals (face electromyogram, skin electrodermal activity, peripheral temperature, and electrocardiogram) in 60 participants with and without misophonia, a condition characterized by decreased tolerance to innocuous sounds. Our goal was to objectively characterize the physiological response to misophonia triggering sounds. We found that misophonic responses can be objectively identified in some cases through atypical physiological reactions to triggering stimuli, though not all participants exhibited this response. Our analyses suggest a large interindividual variability in response to misophonic triggers and highlights the need for methodological adjustments in future experiments to increase the detectability of misophonic …

On The Provenance Of Software Systems: Automating Software Traceability With Knowledge Graph And Large Language Model Synergy, Tyler Procko

Doctoral Dissertations and Master's Theses

The present dissertation delineates a system that enables those engaged in software development to automatically generate and maintain project life cycle provenance. All projects are implemented and made manifest with the development of artifacts, e.g., papers, code files, etc. Tools exist to accelerate artifact creation, but little focus is paid to the processes that produce them. In terms of Ontology, or, from Ancient Greek, the study of being, the two most basic entities in reality are Continuant and Occurrent, or, roughly, “Artifact” and “Process”. This dissertation posits that for any created artifact, its process of creation, i.e., its life …

Painting Rich Six-Dimensional Pictures Using Polarized Fluorescence Microscopy, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

No abstract provided.

Non-Orthogonal Multiple Access Empowered Physical Layer Security Systems: Review, Issues And Challenges, Aml Fawzy, Mahmoud Selim, Maha Elsabrouty, Sameh Napoleon, Mustafa M. Abd Elnaby

Journal of Engineering Research

As 5G networks advance, the demand for higher data rates, enhanced spectral efficiency, and increased connectivity intensify. Non-orthogonal multiple Access (NOMA) addresses these needs by allowing multiple users to share the same time and frequency resources, thus optimizing network resource utilization and significantly boosting system capacity and throughput. NOMA's influence extends beyond traditional communication scenarios, impacting various vertical industries that require extensive connectivity, such as the Internet of Things (IoT). This transformative approach is crucial for industrial and critical mission applications. Given the importance of safeguarding these communications from potential eavesdroppers, Physical Layer Security (PLS) emerges as a vital tool. …

The Impact Of Solar Angle And Cloud Shadows On 3d Reconstruction Of Rolling Stock Cargo, Carlina M. Ostrand, Adam D. Reiman, Frank W. Ciarallo, Scott L. Nykl, Clark N. Taylor, Joshua F. Krutz

Faculty Publications

Meeting the relentless demand for more efficient air cargo transportation is of paramount importance for commercial needs and military missions. This study describes an experiment to test an innovative approach that harnesses cutting-edge stereoscopic vision technology to create 3D point clouds of rolling stock cargo across varying solar angles and cloud shadow conditions. Virtual cargo point clouds are generated by calibrating and systematically organizing the depth and location points from an RGB-D camera and then reprojecting them in a virtual environment. Measurement accuracy was rigorously tested across six camera positions in various combinations of weather conditions against physical ground truth …

Misalignment Uncertainty In Near-Field Thz Scattering Experiments, Philip Patterson

Theses and Dissertations

This research investigates the effect of misalignment on the near-field scattering of cylinders in the 550-700 GHz frequency band. A Type-1 calibration is performed on previously collected data, using a near-field physical optics solution to simulate scattering at various positions and orientations. The alignment of the cylinders at the time of measurement is predicted by comparing the range profiles of the theoretical and calibrated responses. The data with the most similar range profiles had a mean calibration difference metric of -2.78 dB and a standard deviation of -0.57 dB, demonstrating the presence of sources of error that are dominant over …

Statistical Analysis Of Spreading Code Authentication (Sca) Performance Under Varying Signal Conditions And Marker Quantization Schemes, Joseph Quinones-Ocasio

Theses and Dissertations

This thesis analyzes Spreading Code Authentication (SCA) in the GPS L1C signal using the PyChips software-defined receiver (SDR)framework. Monte Carlo simulations evaluate authentication performance under varying signal conditions, assessing the impact of double-precision and quantized data on signal integrity. Results demonstrate that authentication remains achievable at low signal-to-noise ratio(SNR) conditions but introduces trade-offs in memory usage and authentication time. These findings provide insights into optimizing SCAfor resource-constrained environments, contributing to secure GPS operations in critical applications such as aviation, autonomous systems,and national defense.

Deep Learning-Based Gain Estimation For Multi-User Software-Defined Radios In Aircraft Communications, Viraj K. Gajjar, Kurt L. Kosbar

Electrical and Computer Engineering Faculty Research & Creative Works

It may be helpful to integrate multiple aircraft communication and navigation functions into a single software-defined radio (SDR) platform. To transmit these multiple signals, the SDR would first sum the baseband version of the signals. This outgoing composite signal would be passed through a digital-to-analog converter (DAC) before being up-converted and passed through a radio frequency (RF) amplifier. To prevent non-linear distortion in the RF amplifier, it is important to know the peak voltage of the composite. While this is reasonably straightforward when a single modulation is used, it is more challenging when working with composite signals. This paper describes …

Island Nation Duress: Simulating Passive Peer-To-Peer Bluetooth Communication During Disaster Relief, Jason K. Medeiros

Theses and Dissertations

Pacific Islands under U.S. jurisdiction are highly vulnerable to natural disasters, yet many lack the infrastructure to effectively respond and recover. Clear communication during and after such events is critical for evacuation, hazard awareness, and first responders’ coordination. This research explores a simulation-based approach using Bluetooth communication to relay messages across Guam, assessing its efficiency through statistical analysis. By examining regional differences and geographic impacts on Bluetooth messaging, the study aims to identify key factors that enhance peer-to-peer communication for timely and effective disaster response.

Development Of An Advanced 16-Channel High-Fidelity Multi-Frequency Software-Defined Rf Front-End For Advanced Satnav Signal Monitoring Applications, Melbourne T. Ketteridge

Theses and Dissertations

Multi-element antenna array technology provides significant performance advantages in satellite timing and navigation (satnav) receiver applications. It is the most effective anti-jamming method with the ability to place steep nulls in the direction of jammers. Until recently, satnav systems with 4 or more antenna elements were designated as weapons technology and restricted under ITAR regulations. This opens the door to commercial multi-element satnav receivers. Due to advancements in wireless broadband technology a receiver built entirely using commercial off-the-shelf (COTS) components is possible. This thesis presents an architecture for a high fidelity 16-channel RF front-end (RFFE) for research and development of …

Calibration And Demonstration Of A Dropped Channel Polarimetric Compressive Sensing Radar System, Cameron G. Goodbar

Theses and Dissertations

The Air Force Institute of Technology (AFIT) Dropped Channel Polarimetric Compressive Sensing (DCPCS) Radar System is a polarimetric radar utilizing four horn antennae with a unique cross-coupling architecture that enables direct control of system parameters to embed signals into adjacent channels. This thesis characterizes the nature of the system, develops system calibration, and illustrates the performance of the DCPCS technique under multiple system configurations. As shown in the results, DCPCS can successfully reconstruct full-polarization data from a subset of polarization measurements. In many cases, the target estimation and signal reconstruction is precise despite less-than-ideal conditioning of the canonical target dictionary …

Deep Reinforcement Learning For Leo Satellite Grouping, James E. Minteer

Theses and Dissertations

This research investigates jamming evasion using DRL to provide an autonomous solution that repositions a geostationary satellite experiencing directed, terrestrial based jamming. Second, this thesis applies DRL to an area of research for LEO satellite constellations, user grouping, using a portion of an Air Force Research Lab reinforcement learning framework. As LEO satellites orbit the earth, they must constantly re-evaluate not only which users they are able to connect to, but on which of its multiple beams. This model succeeds in finding a balance between maximizing signal strength and minimizing overhead from switching user assignments, all while requiring fewer costly …

Harmonicthreads – An Interface That Supports Accessibility In Musical Interaction, Ellie Nguyen, Miyuki Weldon, Franceli L. Cibrian

Engineering Faculty Articles and Research

Traditional musical instruments often can create boundaries due to their cost, training, mobility, and cognitive requirements, making musical expression inaccessible. To address this challenge, we developed HarmonicThreads, a novel pervasive computing interface consisting of a responsive, flexible fabric. HarmonicThreads provides a tactile and auditory experience, allowing users to easily create and control sounds. Using embedded sensors and real-time processing, HarmonicThreads interprets the user's natural movements and interactions to create adaptable musical outputs. This enables context-aware musical interaction, demonstrating the potential of pervasive interfaces in reducing barriers and making musical expression more accessible.

Increasing Guard Band Size To Decrease Interference In V2x Communication, Nakira Oglesby, Mackenzie Prescott, Billy Kihei, Ph.D.

Symposium of Student Scholars

As technologies evolve and new devices are introduced, the demand for fast and reliable vehicle-to-everything (V2X) communication increases. As this demand increases, the interference level in the 5.9GHz Dedicated Short Range Communications (DSRC) band will inevitably increase. And thus, the task of somehow minimizing this interference becomes increasingly important as time passes. This report investigates the effects of increasing the guard band size of the lower 5.9 GHz DSRC band on the adjacent channel interference from Unlicensed National Information Infrastructure 4 band (U-NII-4) devices and to try and see if there is a significant decrease in the interference level. The …

Novel Electrophysiological Biomarkers In Pediatric Drug Resistant Epilepsy And Genetic Epilepsy Syndromes, Sakar Rijal

Bioengineering Dissertations - Archive

Pediatric epilepsies, particularly those that are drug-resistant or genetically driven, represent some of the most complex neurological disorders encountered in childhood. Central to their pathophysiology is a disruption in the delicate balance between cortical excitation and inhibition (E/I), often resulting from impaired GABAergic interneuron function. This imbalance manifests as aberrant network dynamics and altered neural oscillations, giving rise to seizures and long-term cognitive impairments. In this thesis, we developed a translational framework to identify electrophysiological biomarkers that (i) assess cortical E/I imbalance and (ii) map epileptogenic zones, with the aim of enhancing diagnosis, guiding surgical planning, and informing therapeutic monitoring …

Smart Irrigation System Using Iot And Lstm For Optimal Water Management, Farley Y. Ruiz

Electrical Engineering Theses - Archive

This thesis presents the design and implementation of a smart irrigation system that combines Internet of Things hardware with a Long Short-Term Memory (LSTM) neural network for predictive soil moisture management. The goal is an affordable and reliable solution that uses real-time sensor data and environmental data to schedule irrigation before the substrate moisture drops below its target range. The system integrates soil moisture, temperature, humidity, and sensors on an Arduino Nano that communicates wirelessly with a Raspberry Pi. The Raspberry Pi runs a Python/Flask backend that collects and processes data, executes the LSTM model, and serves a secure web …

Power Quality Event Diagnosis Using Multi-Rate Neural Networks, Jordan D. Lloyd

Electrical Engineering Theses - Archive

Power quality disturbances (PQDs) are among the primary challenges facing modern electrical systems, as they degrade the performance and lifespan of connected equipment. This thesis investigates the relationship between the rate at which voltage waveform data are sampled, the reliability of these measurements, and the ability of deep neural networks to classify PQDs accurately. A one-dimensional convolutional neural network (CNN) was trained and evaluated across multiple sampling rates and signal-to-noise ratios to quantify how information loss in the temporal and spectral domains affects classification reliability. The results demonstrate that model accuracy degrades nonlinearly as sampling rate and signal-to-noise ratio (SNR) …

Revealing Spatiotemporal Neural Activation Patterns In Electrocorticography Recordings Of Human Speech Production By Mutual Information, Julio Kovacs, Dean Krusienski, Minu Maninder, Willy Wriggers

Mechanical & Aerospace Engineering Faculty Publications

Background

Spatiotemporal mapping of neural activity during continuous speech production has been traditionally approached using correlation coefficient (CC) analysis between cortical signals and speech recordings. A prior study employed this approach using electrocorticography (ECoG) data from participants who underwent invasive intracranial monitoring for epilepsy. However, CC cannot detect nonlinear relationships and is dominated by the correspondence between periods of silence and of non-silence.

New Method

We introduce the mutual information (MI) measure, which can capture both linear and nonlinear dependencies. We validated CC and MI on the sub-second spatiotemporal brain activity recorded during continuous speech tasks. To refine the results, …

Study Of Deep Neural Network Trained With Salient, Compressed Medical Video Data For Enhanced Predication, Aileen Sengupta

Electrical Engineering Dissertations - Archive

The rapid growth of surgical video analysis presents a need for efficient deep learning models for surgical training, while reducing the need for excessive image and video image storage. Traditional training approaches typically rely on uniformly compressed video data, instead of selectively preserving the most surgically relevant regions. This dissertation investigates the impact of training deep neural networks (DNNs), both convolutional and transformer-based architectures, on saliency-guided, differentially compressed surgical video sequences. The study systematically evaluates how such compression influences prediction accuracy, computational efficiency and storage requirements. Experimental results demonstrate that models trained on ROI-focused compressed data combined with motion vectors …

Neurovascular Coupling Impairments In Acute Traumatic Brain Injury: An Eeg-Nirs Analysis, Zachary Armstrong

Bioengineering Theses - Archive

Traumatic brain injury (TBI) is a major cause of neurological impairment, often leading to variable recovery and uncertain prognosis in the neurocritical care setting. There is a pressing clinical need for robust, physiologically grounded biomarkers to inform prognosis and therapeutic decision-making in acute TBI. This thesis investigates neurovascular coupling (NVC), the physiological coordination between neuronal activity and cerebral blood flow, as a candidate biomarker for brain function and recovery after injury.

A prospective cohort study was performed using simultaneous electroencephalography (EEG) and near-infrared spectroscopy (NIRS) recordings in patients with moderate-to-severe TBI and healthy controls. Wavelet transform coherence (WTC) analysis was …

A Multiscale Ai Framework For Forest And Agriculture Health Monitoring: Drone-Based Object Recognition And Segmentation For Automated Ecological Assessment, Sruthi Keerthi Valicharla

Graduate Theses, Dissertations, and Problem Reports (ETD)

Forest and agricultural ecosystems are increasingly at risk due to invasive species, pests, and diseases, necessitating scalable, automated, and intelligent monitoring solutions. Traditional field based forest and agriculture health assessments are limited by cost, time, and spatial coverage. This dissertation presents a multiscale deep learning framework that automates forest and agriculture health monitoring using drone imagery and computer vision techniques. The system operates across three spatial levels: forest level, tree level, and leaf level, combining object detection, segmentation, and classification models to support large scale ecological assessment.

At the forest level, high-altitude drone imagery is processed using object detection and …

Transformer-Based Symbolic Music Generation, Ben Buentello

Master’s Theses

This thesis investigates the capacity of transformer-based architectures to learn generalized musical patterns through symbolic generation. To support this exploration, a complete music generation pipeline was developed, beginning with the construction and classification of a large-scale dataset of over 170,000 MIDI files. The dataset was processed using rule-based heuristics and custom neural classifiers to separate tracks by musical function and contour. A novel tokenization scheme, MINTii, was introduced to encode musical information compactly through interval-based representations, reducing redundancy and promoting generalization. Using this infrastructure, a transformer model was trained to generate single-track melodic sequences. Its performance was evaluated through both …

Trace Flight Computer, Zachary Stratton, Vandad Mossavand Varkaneh, Nicholas Ely

Williams Honors College, Honors Research Projects

In the world of collegiate rocketry, there are currently no commercial-off-the-shelf flight computers capable of being fitted to liquid engine rockets with thrust vectoring control. Currently, amateur rocketeers utilize unreliable Arduino-based systems or expensive drone computers. The objective of this project is to design a flight computer capable of data collection and filtering, telemetry transmission, and real-time controls of critical safety systems using readily available commercial-off-the-shelf components to allow rocketeers to complete their designs within a reasonable budget. The system will collect data from two IMUs, a barometric altimeter, and a magnetometer, then filter the collected data using custom Kalman …

Cochlear Electrode Insertion Training Model, Sarah Powell, Kaelyn E. Kraley, Nathan J. Smith

Williams Honors College, Honors Research Projects

Cochlear implant surgery is a delicate procedure performed by Otolaryngologists (ENTs) to implant an electronic device into the inner ear to provide a sense of sound for people who are profoundly deaf or hard of hearing. The current practices of training involve cadavers and 3D-printed models. Cadavers are commonly used but are expensive, single-use, and do not provide visual and haptic feedback, which are essential for medical students. 3D printed models are less commonly used and are hard to fabricate and not as realistic. If medical students are not properly trained for this delicate procedure, then risks are significantly increased …

Vector Estimation For Continuous Tracking Of Observed Radio Signals (V.E.C.T.O.R.) Lunar Navigation System, Dimitry Melnikov, Evan Bartel, Andrew Burrier, Goran Gjorgievski

Williams Honors College, Honors Research Projects

NASA's Artemis program requires precise navigation capabilities to establish the first sustained presence on the lunar surface. However, as launches bring necessary orbital infrastructure, the Artemis program will face a critical period during which reliable lunar navigation is not possible. To address this challenge, the V.E.C.T.O.R. system tracks assets, such as rovers and astronauts, as User Terminals relative to a pre-existing cell tower, or Base Station. To do so, the system leverages existing Base Station hardware to calculate the location of User Terminals in conjunction with existing communications infrastructure.

Scalable Hypergraph Structure Learning With Diverse Smoothness Priors, Benjamin T. Brown

Theses and Dissertations--Electrical and Computer Engineering

In graph signal processing, learning weighted connections between nodes from signals is a fundamental task when the underlying relationships are unknown. With the extension of graphs to hypergraphs, where edges can connect more than two nodes, graph learning methods have similarly been generalized to hypergraphs. However, the absence of a unified framework for calculating total variation has led to divergent definitions of smoothness and, consequently, differing approaches to hyperedge recovery. This challenge is confronted in this work through generalization of several previously proposed hypergraph total variations, allowing ease of substitution into a vector-based optimization. To this end, a novel hypergraph …

Waveforms For Next Generation Non-Stationary Channels, Zhibin Zou

Electronic Theses & Dissertations (2024 - present)

Waveform design aims to achieve orthogonality among data signals/symbols across all available Degrees of Freedom (DoF) to avoid interference while transmitted over the channel. Precoding involves the decomposition of the channel matrix into orthogonal components for the purpose of constructing a precoding matrix that is then combined with the data signal to achieve orthogonality in the spatial dimension. On the other hand, modulation uses orthogonal carriers in a certain signal space to carry data symbols with minimal interference from other symbols. However, it is widely evident that next Generation (xG) wireless systems will experience very high mobility, density and time-varying …

Improving Large Scale Face Recognition With Identity Codes, Mohammad Saeed Ebrahimi Saadabadi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Despite significant advances in deep face recognition, current systems face several practical challenges in real-world scenarios. These include high computational cost of training on large-scale datasets, inefficient use of metric space, and mismatch between training and evaluation frameworks. This dissertation addresses these limitations through three completed studies. The first part presents a research effort aimed at addressing the computational bottlenecks of large-scale FR training. This work proposes a framework that replaces conventional scalar identity labels with structured identity codes, \ie, sequences of tokens optimized to preserve semantic and metric separation. The formulation is designed to reduce the computational cost of …

Neural Network-Based Image Compression, Atefeh Khoshkhahtinat

Graduate Theses, Dissertations, and Problem Reports (ETD)

The rapid advancement of information technology and the exponential growth of digital communication have significantly increased the demand for efficient data compression techniques that reduce storage requirements, minimize bandwidth consumption, and accelerate data transmission—without substantially compromising data quality. This dissertation addresses these challenges by investigating and developing advanced learned image compression (LIC) methods, with a particular focus on lossy compression for both natural images and scientific imagery obtained from NASA’s Solar Dynamics Observatory (SDO) mission. Traditional image compression standards—such as JPEG, JPEG2000, BPG, and HEVC—rely on manually engineered transforms and heuristic rules, which often lack the adaptability required to accommodate …

Green Bank Chime/Frb Outriggers Commissioning And Analog System Development, Kholoud Sharif Tag Alkhatem Khairy

Graduate Theses, Dissertations, and Problem Reports (ETD)

The main objective of this thesis is to document the development and commissioning of the Canadian Hydrogen Intensity Mapping Experiment. (CHIME) outrigger at the Green Bank Observatory. (GBO) in Green Bank, WV. This novel cylindrical wide-field radio transient telescope is currently operating in conjunction with CHIME. The CHIME outrigger at GBO aims to contribute significantly to the field of radio astronomy, with implications for both Fast Radio Burst. (FRB) science and broader astronomical research. The construction and commissioning of the CHIME outrigger at the GBO mark a pivotal step forward in pursuing high-precision wide-field detection and localization of radio transients, …