Signal Processing Commons^™

Radiometric Correction Of Multispectral Cameras Using Photosensor Irradiance For Agronomy Applications, Nicholas S. Mitchell

Electronic Thesis and Dissertation Repository

Cloud coverage has a significant impact on the reflectance maps generated by multispectral cameras mounted on UAV's in small farm settings. The current approach is to calibrate the camera once before every flight and use the radiometric calibration map for the entire flight. In this work we have designed and built a downwelling and upwelling photosensor to work in sync with our custom multispectral camera. A dual reflectance panel implementation for the time dependent radiometric calibration of the multispectral camera is completed. The solar spectral irradiance curve is approximated using the current measurements from the downwelling photosensor and the ground …

Longitudinal Partitioning Waveform Relaxation Methods For The Analysis Of Transmission Line Circuits, Tarik Menkad

Electronic Thesis and Dissertation Repository

Three research projects are presented in this manuscript. Projects one and two describe two waveform relaxation algorithms (WR) with longitudinal partitioning for the time-domain analysis of transmission line circuits. Project three presents theoretical results about the convergence of WR for chains of general circuits.

The first WR algorithm uses a assignment-partition procedure that relies on inserting external series combinations of positive and negative resistances into the circuit to control the speed of convergence of the algorithm. The convergence of the subsequent WR method is examined, and fast convergence is cast as a generic optimization problem in the frequency-domain. An automatic …

Designing And Evaluating Of Mimo Systems For Millimeter-Wave Communications, Mojtaba Ahmadi Almasi

Boise State University Theses and Dissertations

The fifth generation (5G) of wireless communications will integrate all existing technologies while bringing its own to the system. Amongst these technologies, millimeter-wave (mmWave) is emerging as a promising solution for 5G systems. However, to fully harness the potential of mmWave communications, obstacles such as severe path loss, channel sparsity, and hardware complexity should be overcome. The existing cost-effective systems can considerably reduce the hardware complexity and partially severe path loss, while channel sparsity still remains a main problem. Other factors such as transmission reliability and coverage area should be considered in 5G mmWave communications. Non-orthogonal multiple access (NOMA) is …

A Study In Gps-Denied Navigation Using Synthetic Aperture Radar, Colton P. Lindstrom

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

In modern navigation systems, GPS is vital to accurately piloting a vehicle. This is especially true in autonomous vehicles, such as UAVs, which have no pilot. Unfortunately, GPS signals can be easily jammed or spoofed. For example, canyons and urban cities create an environment where the sky is obstructed and make GPS signals unreliable. Additionally, hostile individuals can transmit personal signals intended to block or spoof GPS signals. In these situations, it is important to find a means of navigation that doesn’t rely on GPS.

Navigating without GPS means that other types of sensors or instruments must be used to …

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 …

An Exploratory Study Of Pulse Width And Delta Sigma Modulators, Logan B. Penrod

Master's Theses

This paper explores the noise shaping and noise producing qualities of Delta-Sigma Modulators (DSM) and Pulse-Width Modulators (PWM). DSM has long been dominant in the Delta Sigma Analog-to-Digital Converter (DSADC) as a noise-shaped quantizer and time discretizer, while PWM, with a similar self oscillating structure, has seen use in Class D Power Amplifiers, performing a similar function. It has been shown that the PWM in Class D Amplifiers outperforms the DSM [1], but could this advantage be used in DSADC use-cases? LTSpice simulation and printed circuit board implementation and test are used to present data on four variations of these …

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 …

Health Monitoring Using Deep Learning Of Acoustic And Speech Signals, Eric E. Hamke

Electrical and Computer Engineering ETDs

The focus of the research is to identify stress markers in a firefighter's speech. These markers include changes in breathing patterns and changes in the fundamental frequency of an individual’s voice. The breathing patterns are characterized using the number of breaths taken in a minute and the time spent inhaling. These measures are estimated using a Restricted Boltzmann Machine to process a firefighters’ SCBA regulator sounds, as open and closed. The classifications are then combined into continuous intervals. Observing the length of the intervals and the number of interval-starts represents time spent inhaling and the breathing rates (breaths per minute). …

Parallel And Asynchronous Distributed Optimization For Power Systems Operation, Ali Mohammadi

LSU Doctoral Dissertations

Distributed optimization approaches are gaining more attention for solving power systems energy management functions, such as optimal power flow (OPF). Preserving information privacy of autonomous control entities and being more scalable than centralized approaches are two primary reasons for developing distributed algorithms. Moreover, distributed/ decentralized algorithms potentially increase power systems reliability against failures of components or communication links.

In this dissertation, we propose multiple distributed optimization algorithms and convergence performance enhancement techniques to solve the OPF problem. We present a multi-level optimization algorithm, based on analytical target cascading, to formulate and solve a collaborative transmission and distribution OPF problem. This …

Improving Closely Spaced Dim Object Detection Through Improved Multiframe Blind Deconvolution, Ronald M. Aung

Theses and Dissertations

This dissertation focuses on improving the ability to detect dim stellar objects that are in close proximity to a bright one, through statistical image processing using short exposure images. The goal is to improve the space domain awareness capabilities with the existing infrastructure. Two new algorithms are developed. The first one is through the Neighborhood System Blind Deconvolution where the data functions are separated into the bright object, the neighborhood system, and the background functions. The second one is through the Dimension Reduction Blind Deconvolution, where the object function is represented by the product of two matrices. Both are designed …

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. …

Design Of An Offline Handwriting Recognition System Tested On The Bangla And Korean Scripts, Nishatul Majid

Boise State University Theses and Dissertations

This dissertation presents a flexible and robust offline handwriting recognition system which is tested on the Bangla and Korean scripts. Offline handwriting recognition is one of the most challenging and yet to be solved problems in machine learning. While a few popular scripts (like Latin) have received a lot of attention, many other widely used scripts (like Bangla) have seen very little progress. Features such as connectedness and vowels structured as diacritics make it a challenging script to recognize. A simple and robust design for offline recognition is presented which not only works reliably, but also can be used for …

Learning Deep Architectures For Power Systems Operation And Analysis, Mahdi Khodayar

Electrical Engineering Theses and Dissertations

With the rapid increase in size and computational complexities of power systems, the need for powerful computational models to capture strong patterns from energy datasets is emerged. In this thesis, we provide a comprehensive review on recent advances in deep neural architectures that lead to significant improvements in classification and regression problems in the area of power engineering. Furthermore, we introduce our novel deep learning methodologies proposed for a large variety of applications in this area. First, we present the interval deep probabilistic modeling for wind speed forecasting. Incorporating the Rough Set Theory into deep neural networks, we create an …

Coffee Can Radar System, Dale Coker

Honors Theses

A Radio Detection and Ranging (“radar”) system detects a target and accurately determines its range and velocity using radio frequency (RF) waves. In the presence of a target, these RF waves are reflected, received, and processed. Until recently, radar systems have been too expensive to implement as undergraduate research projects, primarily because of the cost of the associated RF components. Recently, MIT has developed a low-cost radar system as part of an open-source course. Therefore, one objective of this project is to design and construct a radar system based on the MIT design. A further objective is to develop a …

Indoor Positioning Using Acoustic Pseudo-Noise Based Time Difference Of Arrival, Nicholas J. Luong

Master's Theses

The Global Positioning System (GPS) provides good precision on a global scale, but is not suitable for indoor applications. Indoor positioning systems (IPS) aim to provide high precision position information in an indoor environment. IPS has huge market opportunity with a growing number of commercial and consumer applications especially as Internet of Things (IoT) develops. This paper studies an IPS approach using audible sound and pseudo-noise (PN) based time difference of arrival (TDoA). The system’s infrastructure consists of synchronized speakers. The object to be located, or receiver, extracts TDoA information and uses multilateration to calculate its position. The proposed IPS …

Distance Estimation Using Ofdm Signals For Ultrasonic Positioning, Kyman Huang

Master's Theses

This paper describes a method of estimating distance via Time-of-Flight (TOF) measurement using ultrasonic Orthogonal Frequency Division Multiplexing (OFDM) signals. Using OFDM signals allows the signals and their sub-carriers to remain orthogonal to each other while continuously transmitting. This estimation method is based on the change of phase of a traveling wave as it propagates through a medium (air for ultrasonic signals). By using signals containing multiple tones, the phase change between each frequency component is slightly different. This phase difference is dependent on the distance traveled and can thus be used to estimate distance. This paper studies the impact …

The Design, Testing, And Analysis Of A Constant Jammer For The Bluetooth Low Energy (Ble) Wireless Communication Protocol, Aiku Shintani

Master's Theses

The decreasing cost of web-enabled smart devices utilizing embedded processors, sensors, and wireless communication hardware have created an optimal ecosystem for the Internet of Things (IoT). IEEE802.15.4, IEEE802.11ah, WirelessHART, ZigBee Smart Energy, Bluetooth (BT), and Bluetooth Low Energy (BLE) are amongst the most commonly used wireless standards for IoT systems. Each of these standards has tradeoffs concerning power consumption, range of communication, network formation, security, reliability, and ease of implementation. The most widely used standards for IoT are Bluetooth, BLE, and Zigbee. This paper discusses the vulnerabilities in the implementation of the PHY and link layers of BLE. The link …

Exploring Effects Of Background Music In A Serious Game On Attention By Means Of Eeg Signals In Children, Fettah Kiran

LSU Master's Theses

Music and Serious Games are separately useful alternative therapy methods for helping people with a cognitive disorder, including Attention Deficit Hyperactivity Disorder (ADHD). The goal of this thesis is to explore the effect of background music on children with and without ADHD. In this study, a simple Tetris game is designed with Beethoven, Mozart music, and no-music. There are different brainwave techniques for recording; among others, the electroencephalography (EEG) allows for the most efficient use of BCI. We recorded the EEG brain signals of the regular and ADHD subjects who played the Tetris we designed according to our protocol that …

Heel Down And Toe-Off Time Measured With Ultrasonic Doppler System And Force Plate Sensor, Sabin Timsina

Honors Theses

Collie Box is a medical device that measures the gait parameters of the person walk- ing in front of it. This device uses the Ultrasonic Doppler system to extract the heel-contact and toe-off times of a person walking within the range of 2-10 meters. These times are used to determine the leg’s swing phase and double stance times. The ultrasonic transducer of 10mm diameter is driven at 40kHz. At the time of the heel-contact and toe-off, foot velocity is zero while the torso part of the human body is still in motion. The wide directivity of 10mm diameter ultrasonic transducer …

Methods Of High-Fidelity, High-Efficiency Class-D Audio Amplification, Kaleb Kassaw

Electrical Engineering Undergraduate Honors Theses

Gallium nitride-based field effect transistors (FETs) have opened a path for full-frequency-range class-D audio amplifiers with low distortion and noise, thanks to their ability to switch at much higher frequencies than that of the upper range of human hearing. Compared to traditional silicon-based transistors, GaN-based transistors offer superior efficiencies, particularly at power levels below their maxima. Paired with an analog-to-digital converter, digital signal processor, and pulse-code modulation to pulse-width modulation converter, these transistors are used to design and implement a solid-state amplifier capable of generating 100 watts of output through speakers with an impedance of 8 ohms using a 1-volt …

A Power Constrained 433-Mhz Low Noise Amplifier, Pablo Alvarez Arellano

Graduate Theses and Dissertations

Within wireless communication systems, low noise amplifiers are critical for the performance of receivers. They are primarily responsible for providing enough gain while adding little noise to overcome the noise of the subsequent stages. The LNA presented here is part of a battery-powered transceiver meant to measure crop nutrient data and relay the information. Therefore, power consumption and area become import considerations. To design for a specific power level, a power-constrained noise optimization method is used. The method sizes the amplifying transistor for a fixed source impedance, power dissipation, technology, and operating frequency. The chosen topology is the cascode stage …

An Fpga-Based Hardware Accelerator For The Digital Image Correlation Engine, Keaten Stokke

Graduate Theses and Dissertations

The work presented in this thesis was aimed at the development of a hardware accelerator for the Digital Image Correlation engine (DICe) and compare two methods of data access, USB and Ethernet. The original DICe software package was created by Sandia National Laboratories and is written in C++. The software runs on any typical workstation PC and performs image correlation on available frame data produced by a camera. When DICe is introduced to a high volume of frames, the correlation time is on the order of days. The time to process and analyze data with DICe becomes a concern when …

Development Of Fully Balanced Ssfp And Computer Vision Applications For Mri-Assisted Radiosurgery (Mars), Jeremiah Sanders

Dissertations & Theses (Open Access)

Prostate cancer is the second most common cancer in men and the second-leading cause of cancer death in men. Brachytherapy is a highly effective treatment option for prostate cancer, and is the most cost-effective initial treatment among all other therapeutic options for low to intermediate risk patients of prostate cancer. In low-dose-rate (LDR) brachytherapy, verifying the location of the radioactive seeds within the prostate and in relation to critical normal structures after seed implantation is essential to ensuring positive treatment outcomes.

One current gap in knowledge is how to simultaneously image the prostate, surrounding anatomy, and radioactive seeds within the …

Reinforcement Learning In Self Organizing Cellular Networks, Roohollah Amiri

Boise State University Theses and Dissertations

Self-organization is a key feature as cellular networks densify and become more heterogeneous, through the additional small cells such as pico and femtocells. Self- organizing networks (SONs) can perform self-configuration, self-optimization, and self-healing. These operations can cover basic tasks such as the configuration of a newly installed base station, resource management, and fault management in the network. In other words, SONs attempt to minimize human intervention where they use measurements from the network to minimize the cost of installation, configuration, and maintenance of the network. In fact, SONs aim to bring two main factors in play: intelligence and autonomous adaptability. …

Robust Control Of Burst Suppression Amid Physical And Neurological Uncertainty, Stephen Ampleman, Shinung Ching

McKelvey School of Engineering Theses & Dissertations

Burst suppression is a clinical term describing a phenomenon in which the electroencephalogram (EEG) of a sedated patient produces behavior that switches between higher frequency and amplitude bursting to lower frequency and lower amplitude suppression. This phenomenon can be observed during general anesthesia, hypothermia, or in an otherwise induced coma state. In a clinical setting, this phenomenon is typically induced by sedation from a drug such as propofol (2,6-diisopropylphenol). The level of sedation can be quantified by something called the burst suppression ratio (BSR), which is defined as the amount of time that a patient’s EEG is in a suppressed …

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

Chancellor’s Honors Program Projects

No abstract provided.

Compressive Parameter Estimation Via Approximate Message Passing, Shermin Hamzehei

Masters Theses

The literature on compressive parameter estimation has been mostly focused on the use of sparsity dictionaries that encode a discretized sampling of the parameter space; these dictionaries, however, suffer from coherence issues that must be controlled for successful estimation. To bypass such issues with discretization, we propose the use of statistical parameter estimation methods within the Approximate Message Passing (AMP) algorithm for signal recovery. Our method leverages the recently proposed use of custom denoisers in place of the usual thresholding steps (which act as denoisers for sparse signals) in AMP. We introduce the design of analog denoisers that are based …

Virtual Satcom, Long Range Broadband Digital Communications, Dennis George Watson

Electrical & Computer Engineering Theses & Dissertations

The current naval strategy is based on a distributed force, networked together with high-speed communications that enable operations as an intelligent, fast maneuvering force. Satellites, the existing network connector, are weak and vulnerable to attack. HF is an alternative, but it does not have the information throughput to meet the distributed warfighting need. The US Navy does not have a solution to reduce dependency on space-based communication systems while providing the warfighter with the required information speed.

Virtual SATCOM is a solution that can match satellite communications (SATCOM) data speed without the vulnerable satellite. It is wireless communication on a …

Deep Cellular Recurrent Neural Architecture For Efficient Multidimensional Time-Series Data Processing, Lasitha S. Vidyaratne

Electrical & Computer Engineering Theses & Dissertations

Efficient processing of time series data is a fundamental yet challenging problem in pattern recognition. Though recent developments in machine learning and deep learning have enabled remarkable improvements in processing large scale datasets in many application domains, most are designed and regulated to handle inputs that are static in time. Many real-world data, such as in biomedical, surveillance and security, financial, manufacturing and engineering applications, are rarely static in time, and demand models able to recognize patterns in both space and time. Current machine learning (ML) and deep learning (DL) models adapted for time series processing tend to grow in …

Anti-Jam Gps Controlled Reception Pattern Antennas For Man-Portable Applications, Jeffrey A. Maloney

Doctoral Dissertations

Military GPS receivers provide crucial information to soldiers in the field, however, the performance of these devices is degraded by in band RF interference, making GPS susceptible to jamming. Anti-jam techniques for aircraft and vehicular platforms have been developed, but at present there is no system for dismounted soldiers. There is a need for an anti-jam system which meets the demands of a dismounted soldier and conforms to the size, weight, and power requirements of a portable device. A controlled reception pattern antenna, or CRPA, is a potential solution for jammer mitigation. These devices work by steering reception pattern nulls …