Signal Processing Commons^™

Power System Transients: Impacts Of Non-Ideal Sensors On Measurement-Based Applications, Aaron Wilson

Doctoral Dissertations

The power system is comprised of thousands of lines, generation sources, transformers, and other equipment responsible for servicing millions of customers. Such a complex apparatus requires constant monitoring and protection schemes capable of keeping the system operational, reliable, and resilient. To achieve these goals, measurement is a critical role in the continued functionality of the power system. However, measurement devices are never completely reliable, and are susceptible to inherent irregularities; imparting potentially misleading distortions on measurements containing high-frequency components. This dissertation analyzes some of these effects, as well as the way they may impact certain applications in the grid that …

Remote Human Vital Sign Monitoring Using Multiple-Input Multiple-Output Radar At Millimeter-Wave Frequencies, Toan Khanh Vo Dai

Doctoral Dissertations

Non-contact respiration rate (RR) and heart rate (HR) monitoring using millimeter-wave (mmWave) radars has gained lots of attention for medical, civilian, and military applications. These mmWave radars are small, light, and portable which can be deployed to various places. To increase the accuracy of RR and HR detection, distributed multi-input multi-output (MIMO) radar can be used to acquire non-redundant information of vital sign signals from different perspectives because each MIMO channel has different fields of view with respect to the subject under test (SUT). This dissertation investigates the use of a Frequency Modulated Continuous Wave (FMCW) radar operating at 77-81 …

Efficient Deep Learning And Its Applications, Zi Wang

Doctoral Dissertations

Deep neural networks (DNNs) have achieved huge successes in various tasks such as object classification and detection, image synthesis, game-playing, and biological developmental system simulation. State-or-the-art performance on these tasks is usually achieved by designing deeper and wider DNNs with the cost of huge storage size and high computational complexity. However, the over-parameterization problem of DNNs constrains their deployment in resource-limited devices, such as drones and mobile phones.

With these concerns, many network compression approaches are developed, such as quantization, neural architecture search, network pruning, and knowledge distillation. These approaches reduce the sizes and computational costs of DNNs while maintaining …

Non-Contact Heart Rate Estimation In Low Snr Environments Using Mmwave Radar, Chandler J. Bauder, Aly E. Fathy

Faculty Publications and Other Works -- EECS

Extracting accurate heart rate estimates of human subjects from a distance in high-noise scenarios using radar is a common problem. Often, frequency components from sources such as movement and vital signs from other subjects can overpower the weak reflected signal of the heart. In this study, we propose a signal processing scheme using a state-of-the-art Adaptive Multi-Trace Carving algorithm (AMTC) to accurately detect the heart rate signal over time in non-ideal scenarios. In our initial proof-of-concept results, we show a low heart rate estimation mean absolute error (MAE) of 3bpm for a single subject marching in place and less than …

Non-Contact Techniques For Human Vital Sign Detection And Gait Analysis, Farnaz Foroughian

Doctoral Dissertations

Human vital signs including respiratory rate, heart rate, oxygen saturation, blood pressure, and body temperature are important physiological parameters that are used to track and monitor human health condition. Another important biological parameter of human health is human gait. Human vital sign detection and gait investigations have been attracted many scientists and practitioners in various fields such as sport medicine, geriatric medicine, bio-mechanic and bio-medical engineering and has many biological and medical applications such as diagnosis of health issues and abnormalities, elderly care and health monitoring, athlete performance analysis, and treatment of joint problems. Thoroughly tracking and understanding the normal …

Towards Secure Deep Neural Networks For Cyber-Physical Systems, Jiangnan Li

Doctoral Dissertations

In recent years, deep neural networks (DNNs) are increasingly investigated in the literature to be employed in cyber-physical systems (CPSs). DNNs own inherent advantages in complex pattern identifying and achieve state-of-the-art performances in many important CPS applications. However, DNN-based systems usually require large datasets for model training, which introduces new data management issues. Meanwhile, research in the computer vision domain demonstrated that the DNNs are highly vulnerable to adversarial examples. Therefore, the security risks of employing DNNs in CPSs applications are of concern.

In this dissertation, we study the security of employing DNNs in CPSs from both the data domain …

Machine Learning With Topological Data Analysis, Ephraim Robert Love

Doctoral Dissertations

Topological Data Analysis (TDA) is a relatively new focus in the fields of statistics and machine learning. Methods of exploiting the geometry of data, such as clustering, have proven theoretically and empirically invaluable. TDA provides a general framework within which to study topological invariants (shapes) of data, which are more robust to noise and can recover information on higher dimensional features than immediately apparent in the data. A common tool for conducting TDA is persistence homology, which measures the significance of these invariants. Persistence homology has prominent realizations in methods of data visualization, statistics and machine learning. Extending ML with …

Camera-Based Remote Photoplethysmography For Estimation Of Heart Rate Using Single Board Computers, Benjamin Sweely

Masters Theses

The objective of this project was to develop a wireless, noncontact monitoring system that measures multiple physiological parameters in human faces from a distance using a camera. Compared to traditional sensors, this monitoring system does not use wires or adhesives, providing a safer, more user-friendly application. The goal of the monitoring systems was to estimate heart rate (HR). The current practices of measuring HR involve collecting electrocardiogram (ECG) signals from adhesive electrodes placed on various parts of the body and using a pulse oximeter (PO) typically placed on the ear lobe or finger. We were able to successfully create 2 …

Early Warning Solar Storm Prediction, Ian D. Lumsden, Marvin Joshi, Matthew Smalley, Aiden Rutter, Ben Klein

Chancellor’s Honors Program Projects

No abstract provided.

Torch Mounted Wire Nipper, Steven D. Patrick, Matt Montgomery, Ben Rouse, Garrett D. Foust

Chancellor’s Honors Program Projects

No abstract provided.

Software Defined Radar For Vital Sign Detection, Chandler J. Bauder, James Bates, Steven Engel, James S. Tucker, Fangzhou Liu

Chancellor’s Honors Program Projects

No abstract provided.

Learning Multimodal Structures In Computer Vision, Ali Taalimi

Doctoral Dissertations

A phenomenon or event can be received from various kinds of detectors or under different conditions. Each such acquisition framework is a modality of the phenomenon. Due to the relation between the modalities of multimodal phenomena, a single modality cannot fully describe the event of interest. Since several modalities report on the same event introduces new challenges comparing to the case of exploiting each modality separately.

We are interested in designing new algorithmic tools to apply sensor fusion techniques in the particular signal representation of sparse coding which is a favorite methodology in signal processing, machine learning and statistics to …

Computational Imaging Approach To Recovery Of Target Coordinates Using Orbital Sensor Data, Michael D. Vaughan

Doctoral Dissertations

This dissertation addresses the components necessary for simulation of an image-based recovery of the position of a target using orbital image sensors. Each component is considered in detail, focusing on the effect that design choices and system parameters have on the accuracy of the position estimate. Changes in sensor resolution, varying amounts of blur, differences in image noise level, selection of algorithms used for each component, and lag introduced by excessive processing time all contribute to the accuracy of the result regarding recovery of target coordinates using orbital sensor data.

Using physical targets and sensors in this scenario would be …

Wide-Area Measurement-Driven Approaches For Power System Modeling And Analytics, Hesen Liu

Doctoral Dissertations

This dissertation presents wide-area measurement-driven approaches for power system modeling and analytics. Accurate power system dynamic models are the very basis of power system analysis, control, and operation. Meanwhile, phasor measurement data provide first-hand knowledge of power system dynamic behaviors. The idea of building out innovative applications with synchrophasor data is promising.

Taking advantage of the real-time wide-area measurements, one of phasor measurements’ novel applications is to develop a synchrophasor-based auto-regressive with exogenous inputs (ARX) model that can be updated online to estimate or predict system dynamic responses.

Furthermore, since auto-regressive models are in a big family, the ARX model …

A Quantitative Measure Of Mono-Componentness For Time-Frequency Analysis, Austin P. Albright

Doctoral Dissertations

Joint time-frequency (TF) analysis is an ideal method for analyzing non-stationary signals, but is challenging to use leading to it often being neglected. The exceptions being the short-time Fourier transform (STFT) and spectrogram. Even then, the inability to have simultaneously high time and frequency resolution is a frustrating issue with the STFT and spectrogram. However, there is a family of joint TF analysis techniques that do have simultaneously high time and frequency resolution – the quadratic TF distribution (QTFD) family. Unfortunately, QTFDs are often more troublesome than beneficial. The issue is interference/cross-terms that causes these methods to become so difficult …

An Innovative Approach To Johnson Noise Thermometry By Means Of Spectral Estimation, Nora Dianne Bull

Doctoral Dissertations

Instrumentation in a nuclear power plant is critical in monitoring the stability and safety levels of a reactor. Temperature is a key measurement performed on the core of a reactor to control the power output and sustain a safe thermal margin. If there is a dramatic change in temperature, failure is likely to follow if action is not taken to cool the system. Traditionally, to measure the temperature of a reactor, several resistance temperature detectors are placed in predefined locations on the system. Resistance temperature detectors (RTD) are typically platinum coiled wire wrapped around a ceramic cylinder and encased in …

Face Centered Image Analysis Using Saliency And Deep Learning Based Techniques, Rui Guo

Doctoral Dissertations

Image analysis starts with the purpose of configuring vision machines that can perceive like human to intelligently infer general principles and sense the surrounding situations from imagery. This dissertation studies the face centered image analysis as the core problem in high level computer vision research and addresses the problem by tackling three challenging subjects: Are there anything interesting in the image? If there is, what is/are that/they? If there is a person presenting, who is he/she? What kind of expression he/she is performing? Can we know his/her age? Answering these problems results in the saliency-based object detection, deep learning structured …

Magnetic Local Positioning System With Supplemental Magnetometer-Accelerometer Data Fusion, Benjamin Scott Prothro

Doctoral Dissertations

Geo-location and tracking technology, once confined to the industrial and military sectors, have been widely proliferated to the consumer world since early in the twenty-first century. The commoditization of Global Positioning System (GPS) and inertial measurement integrated circuits has made this possible, with devices small enough to fit in a cellular phone. However, GPS technology is not without its drawbacks: Its power use is high, and it can fail in smaller, obstructed spaces. Magnetic positioning, which exploits the magnetic field coupling between a set of transmitter beacon coils and a set of receiver coils, is an often overlooked, complementary technology …

Exploiting Cross Domain Relationships For Target Recognition, Wei Wang

Doctoral Dissertations

Cross domain recognition extracts knowledge from one domain to recognize samples from another domain of interest. The key to solving problems under this umbrella is to find out the latent connections between different domains. In this dissertation, three different cross domain recognition problems are studied by exploiting the relationships between different domains explicitly according to the specific real problems.

First, the problem of cross view action recognition is studied. The same action might seem quite different when observed from different viewpoints. Thus, how to use the training samples from a given camera view and perform recognition in another new view …

Compressed Sensing In Resource-Constrained Environments: From Sensing Mechanism Design To Recovery Algorithms, Shuangjiang Li

Doctoral Dissertations

Compressed Sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for reconstruction. It is promising that CS can be utilized in environments where the signal acquisition process is extremely difficult or costly, e.g., a resource-constrained environment like the smartphone platform, or a band-limited environment like visual sensor network (VSNs). There are several challenges to perform sensing due to the characteristic of these platforms, including, for example, needing active user involvement, computational and storage limitations and lower transmission capabilities. This dissertation focuses on the study of …

Ultra-Low-Power Configurable Analog Signal Processor For Wireless Sensors, James Kelly Griffin

Masters Theses

The demand for on-chip low-power Complementary Metal Oxide Semiconductor (CMOS) analog signal processing has significantly increased in recent years. Digital signal processors continue to shrink in size as transistors half in size every two years. However, digital signal processors (DSP's) notoriously use more power than analog signal processors (APS's). This thesis presents a configurable analog signal processor (CASP) used for wireless sensors. This CASP contains a multitude of processing blocks include the following: low pass filter (LPF), high pass filter (HPF) integrator, differentiator, operational transconductance amplifier (OTA), rectifier with absolute value functionality, and multiplier. Each block uses current-mode processing and …

Statistical Analysis Of Disturbances In Power Transmission Systems, Liu Liu

Masters Theses

Disturbance analysis is essential to the study of the power transmission systems. Traditionally, disturbances are described as megawatt (MW) events, but the access to data is inefficient due to the slow installation and authorization process of the monitoring device. In this paper, we propose a novel approach to disturbance analysis conducted at the distribution level by exploiting the frequency recordings from Frequency Disturbance Recorders (FDRs) of the Frequency Monitoring Network (FNET/GridEye), based on the relationship between frequency change and the power loss of disturbances - linearly associated by the Frequency Response. We first analyze the real disturbance records of North …

Object Tracking By Pan Tilt System, Lily Hoang

Chancellor’s Honors Program Projects

No abstract provided.

Improved Forensic Medical Device Security Through Eating Detection, Nathan Lee Henry

Masters Theses

Patients are increasingly reliant on implantable medical device systems today. For patients with diabetes, an implantable insulin pump system or artificial pancreas can greatly improve quality of life. As with any device, these devices can and do suffer from software and hardware issues, often reported as a safety event. For a forensic investigator, a safety event is indistinguishable from a potential security event. In this thesis, we show a new sensor system that can be transparently integrated into existing and future electronic diabetes therapy systems while providing additional forensic data to help distinguish between safety and security events. We demonstrate …

A Novel Authentication Method Using Multi-Factor Eye Gaze, Lucas A. Herrera

Masters Theses

A method for novel, rapid and robust one-step multi-factor authentication of a user is presented, employing multi-factor eye gaze. The mobile environment presents challenges that render the conventional password model obsolete. The primary goal is to offer an authentication method that competitively replaces the password, while offering improved security and usability. This method and apparatus combine the smooth operation of biometric authentication with the protection of knowledge based authentication to robustly authenticate a user and secure information on a mobile device in a manner that is easily used and requires no external hardware. This work demonstrates a solution comprised of …

Analysis, Segmentation And Prediction Of Knee Cartilage Using Statistical Shape Models, Joseph Michael Johnson

Doctoral Dissertations

Osteoarthritis (OA) of the knee is one of the leading causes of chronic disability (along with the hip). Due to rising healthcare costs associated with OA, it is important to fully understand the disease and how it progresses in the knee. One symptom of knee OA is the degeneration of cartilage in the articulating knee. The cartilage pad plays a major role in painting the biomechanical picture of the knee. This work attempts to quantify the cartilage thickness of healthy male and female knees using statistical shape models (SSMs) for a deep knee bend activity. Additionally, novel cartilage segmentation from …

Bayesian Dictionary Learning For Single And Coupled Feature Spaces, Li He

Doctoral Dissertations

Over-complete bases offer the flexibility to represent much wider range of signals with more elementary basis atoms than signal dimension. The use of over-complete dictionaries for sparse representation has been a new trend recently and has increasingly become recognized as providing high performance for applications such as denoise, image super-resolution, inpaiting, compression, blind source separation and linear unmixing. This dissertation studies the dictionary learning for single or coupled feature spaces and its application in image restoration tasks. A Bayesian strategy using a beta process prior is applied to solve both problems.

Firstly, we illustrate how to generalize the existing beta …

Novel Applications For Phasor Measurement Units And Synchrophasor Data, Bradley Kerwin Greene

Masters Theses

The last decade has seen an intensified effort towards an improved, technologically advanced electric grid. This effort is largely in part to the need for cleaner and renewable sources of energy. Another motivator for this “smarter grid” is the need for a more reliable and efficiently operated of the wide scale electric infrastructure. The impact of these changes can expect to be seen at both the transmission and distribution level. At the transmission level phasor measurement units and synchrophasor data has emerged as one of the most enabling technologies for the smart grid movement. These devices measure and time synchronize, …

A Low-Power, Highly Stabilized Three-Electrode Potentiostat Using Subthreshold Techniques, Melika Roknsharifi

Doctoral Dissertations

Implantable micro- and nano- sensors and implantable microdevices (IMDs) have demonstrated potential for monitoring various physiological parameters such as glucose, lactate, CO₂ [carbon dioxide], pH, etc. Potentiostats are essential components of electrochemical sensors such as glucose monitoring devices for diabetic patients. Diabetes is a metabolic disorder associated with insufficient production or inefficient utilization of insulin. The most important role of this enzyme is to regulate the metabolic breakdown of glucose generating the necessary energy for human activities. Diabetic patients typically monitor their blood glucose levels by pricking a fingertip with a lancing device and applying the blood to a …

Techniques For Wireless Channel Modeling In Harsh Environments, Phani Teja Kuruganti

Doctoral Dissertations

With the rapid growth in the networked environments for different industrial, scientific and defense applications, there is a vital need to assure the user or application a certain level of Quality of Service (QoS). Environments like the industrial environment are particularly harsh with interference from metal structures (as found in the manufacturing sector), interference generated during wireless propagation, and multipath fading of the radio frequency (RF) signal all invite novel mitigation techniques. The challenge of achieving the benefits like improved energy efficiency using wireless is closely coupled with maintaining network QoS requirements. Assessment and management of QoS needs to occur, …