Open Access. Powered by Scholars. Published by Universities.®

Signal Processing Commons

Open Access. Powered by Scholars. Published by Universities.®

1,656 Full-Text Articles 2,082 Authors 994,183 Downloads 98 Institutions

All Articles in Signal Processing

Faceted Search

1,656 full-text articles. Page 5 of 60.

Enhancing Traffic Safety In Unpredicted Environments With Integration Of Adas Features With Sensor Fusion In Intelligent Electric Vehicle Platform With Implementation Of Environmental Mapping Technology, David S. Obando Ortegon 2023 Georgia Southern University

Enhancing Traffic Safety In Unpredicted Environments With Integration Of Adas Features With Sensor Fusion In Intelligent Electric Vehicle Platform With Implementation Of Environmental Mapping Technology, David S. Obando Ortegon

Electronic Theses and Dissertations

A major objective on society is to reduce the number of accidents and fatalities on the road for drivers, and pedestrians. Therefore, the automotive engineering field is working on this problem through the development and integration of safety technologies such as advanced driving assistance systems. For this reason, this work was intended to develop and evaluate the performance of different ADAS features and IV technologies under unexpected scenarios. This by the development of safety algorithms applied to the intelligent electric vehicle designed and built in this work, through the use of ADAS sensors based on sensor fusion. Evaluation of AEB, …


Predicting Jamming Systems Frequency Hopping Sequences Using Artificial Neural Networks, Charles Strickland 2023 Georgia Southern University

Predicting Jamming Systems Frequency Hopping Sequences Using Artificial Neural Networks, Charles Strickland

Electronic Theses and Dissertations

This work proposes a neural network architecture that was designed to predict and reverse engineer frequency hopping jamming systems. The neural network was initially optimized for use with a 12th order linear shift feedback register maximum length sequence utilizing a minimal polynomial as the characteristic polynomial. This neural network was then scaled to accommodate 7 different sequences, of orders 6 through 12. The neural network was trained for these sequences using training data that is 10 times the length of the sequence. This information is then used to generate a hopping sequence that reduces the jamming interference to 0 with …


Ads-B Communication Interference In Air Traffic Management, George Ray 2023 Shepherd University

Ads-B Communication Interference In Air Traffic Management, George Ray

International Journal of Aviation, Aeronautics, and Aerospace

Automated Dependent Surveillance Broadcast (ADS-B) provides position and state information about aircraft and is becoming an essential component in the global air traffic management system. ADS-B transponders broadcast this key information on a common frequency to both other aircraft and to secondary surveillance radar systems located at ground stations. Both the aircraft transponders and the ground stations work together to assist in managing the commercial airspace. Since the aircraft transponders all broadcast on the same frequency and are in close proximity there is an apparent risk of interference and the garbling of the communications needed to manage the airspace.

The …


Computational Mechanisms Of Face Perception, Jinge Wang 2023 West Virginia University

Computational Mechanisms Of Face Perception, Jinge Wang

Graduate Theses, Dissertations, and Problem Reports

The intertwined history of artificial intelligence and neuroscience has significantly impacted their development, with AI arising from and evolving alongside neuroscience. The remarkable performance of deep learning has inspired neuroscientists to investigate and utilize artificial neural networks as computational models to address biological issues. Studying the brain and its operational mechanisms can greatly enhance our understanding of neural networks, which has crucial implications for developing efficient AI algorithms. Many of the advanced perceptual and cognitive skills of biological systems are now possible to achieve through artificial intelligence systems, which is transforming our knowledge of brain function. Thus, the need for …


Evaluation Of Lidar Uncertainty And Applications Towards Slam In Off-Road Environments, Zachary D. Jeffries 2023 Michigan Technological University

Evaluation Of Lidar Uncertainty And Applications Towards Slam In Off-Road Environments, Zachary D. Jeffries

Dissertations, Master's Theses and Master's Reports

Safe and robust operation of autonomous ground vehicles in all types of conditions and environment necessitates complex perception systems and unique, innovative solutions. This work addresses automotive lidar and maximizing the performance of a simultaneous localization and mapping stack. An exploratory experiment and an open benchmarking experiment are both presented. Additionally, a popular SLAM application is extended to use the type of information gained from lidar characterization, demonstrating the performance gains and necessity to tightly couple perception software and sensor hardware. The first exploratory experiment collects data from child-sized, low-reflectance targets over a range from 15 m to 35 m. …


Enhancing Vehicular Perception: A Comprehensive Analysis Of Sensor Fusion Performance Through Weighted Averages And Fuzzy C-Means For Optimal Data Association, Zachary Brian Flanigan 2023 West Virginia University

Enhancing Vehicular Perception: A Comprehensive Analysis Of Sensor Fusion Performance Through Weighted Averages And Fuzzy C-Means For Optimal Data Association, Zachary Brian Flanigan

Graduate Theses, Dissertations, and Problem Reports

This work explores the implementation of sensor fusion and data association for autonomous vehicle design. Advancements in Adaptive Driver Assistance System (ADAS) technology have driven the development of perception algorithms required for higher levels of autonomy in vehicles. Perception algorithms process data collected from radar, camera, and LiDAR sensors to generate a complete model of the ego vehicle’s surrounding environment. Fusion of data from these sensors is important for accurate measurement of longitudinal and lateral distances to surrounding objects. Sensor fusion associates sensor detections to each other through different data association techniques. Data association techniques can consist of independent assignment …


Automatic Optical Inspection-Based Pcb Fault Detection Using Image Processing, Shruti Rajiv Vaidya 2023 Michigan Technological University

Automatic Optical Inspection-Based Pcb Fault Detection Using Image Processing, Shruti Rajiv Vaidya

Dissertations, Master's Theses and Master's Reports

Increased Printed Circuit Board (PCB) route complexity and density combined with the growing demand for low-scale rapid prototyping has increased the desire for Automated Optical Inspection (AOI) that reduces prototyping time and production costs by detecting defects early in the production process. Traditional defect detection method of human visual inspection is not only error prone but is also time-consuming given the growing complex and dense circuitry of modern-day electronics. Electric contact-based testing, either in the form of a bed of nails testing fixture or a flying probe system, is costly for low-rate rapid prototyping. An AOI is a non-contact test …


Botsitter, Maria Hatzis, Gregory Blondheim Jr., Marian Bonto, Brett Jacobsen 2023 The University of Akron

Botsitter, Maria Hatzis, Gregory Blondheim Jr., Marian Bonto, Brett Jacobsen

Williams Honors College, Honors Research Projects

As society progresses into an era where both parents work, whether it is online or in person, children in the home may be put in dangerous situations if they are not given the attention they need. The BotSitter is an automated system that follows the child around and makes an audio alarm to alert both the child and the nearby guardian. Using RSSI trilateration, predetermined danger areas, and embedded controls, the BotSitter will be able to follow the child. The device can manage to keep track of the child for the guardian while being almost completely automated outside of setup.


Deep-Learning-Based Classification Of Digitally Modulated Signals Using Capsule Networks And Cyclic Cumulants, John A. Snoap, Dimitrie C. Popescu, James A. Latshaw, Chad M. Spooner 2023 Old Dominion University

Deep-Learning-Based Classification Of Digitally Modulated Signals Using Capsule Networks And Cyclic Cumulants, John A. Snoap, Dimitrie C. Popescu, James A. Latshaw, Chad M. Spooner

Electrical & Computer Engineering Faculty Publications

This paper presents a novel deep-learning (DL)-based approach for classifying digitally modulated signals, which involves the use of capsule networks (CAPs) together with the cyclic cumulant (CC) features of the signals. These were blindly estimated using cyclostationary signal processing (CSP) and were then input into the CAP for training and classification. The classification performance and the generalization abilities of the proposed approach were tested using two distinct datasets that contained the same types of digitally modulated signals, but had distinct generation parameters. The results showed that the classification of digitally modulated signals using CAPs and CCs proposed in the paper …


Wifi Sensing At The Edge Towards Scalable On-Device Wireless Sensing Systems, Steven M. Hernandez 2023 Virginia Commonwealth University

Wifi Sensing At The Edge Towards Scalable On-Device Wireless Sensing Systems, Steven M. Hernandez

Theses and Dissertations

WiFi sensing offers a powerful method for tracking physical activities using the radio-frequency signals already found throughout our homes and offices. This novel sensing modality offers continuous and non-intrusive activity tracking since sensing can be performed (i) without requiring wearable sensors, (ii) outside the line-of-sight, and even (iii) through the wall. Furthermore, WiFi has become a ubiquitous technology in our computers, our smartphones, and even in low-cost Internet of Things devices. In this work, we consider how the ubiquity of these low-cost WiFi devices offer an unparalleled opportunity for improving the scalability of wireless sensing systems. Thus far, WiFi sensing …


Modeling The Early Visual System, Nicholas Lanning 2023 University of Kentucky

Modeling The Early Visual System, Nicholas Lanning

Theses and Dissertations--Electrical and Computer Engineering

There are two encoding schema present in simple cells in the early visual system of vertebrates: the retinal simple cells activate highly when the receptive field contains a center surround stimulus, while the primary visual cortex’s (V1) simple cells activate highly when the receptive field contains visual edges. Work has been done in the past to enforce constraints on visual machine learning such that the retinal or V1 encoding is learned, but this work is often done to emulate retinal and V1 encoding in a vacuum. Recent work using convolutional neural networks focuses on anatomical constraints along with a supervised …


Application Of Distributed Fiber-Optic Sensing For Pressure Predictions And Multiphase Flow Characterization, Gerald Kelechi Ekechukwu 2022 Louisiana State University and Agricultural and Mechanical College

Application Of Distributed Fiber-Optic Sensing For Pressure Predictions And Multiphase Flow Characterization, Gerald Kelechi Ekechukwu

LSU Doctoral Dissertations

In the oil and gas industry, distributed fiber optics sensing (DFOS) has the potential to revolutionize well and reservoir surveillance applications. Using fiber optic sensors is becoming increasingly common because of its chemically passive and non-magnetic interference properties, the possibility of flexible installations that could be behind the casing, on the tubing, or run on wireline, as well as the potential for densely distributed measurements along the entire length of the fiber. The main objectives of my research are to develop and demonstrate novel signal processing and machine learning computational techniques and workflows on DFOS data for a variety of …


In Band Full Duplex For Wireless Communication, A Medium Access Control Perspective, Yazeed Alkhrijah 2022 Southern Methodist University

In Band Full Duplex For Wireless Communication, A Medium Access Control Perspective, Yazeed Alkhrijah

Electrical Engineering Theses and Dissertations

In-band full duplex (IBFD) for wireless communication is defined as the ability of a node to send and receive data simultaneously by using the same frequency band. IBFD has the potential to double the spectral efficiency of wireless networks. In addition, IBFD improves security by mystifying any eavesdropper with multiple transmitted signals in a single frequency. Also, IBFD reduces the end-to-end transmission delay and solves the hidden terminal and exposed terminal problems. However, IBFD suffers from self-interference. Canceling self-interference (SI) is the main challenge in enabling IBFD. Another challenge for IBFD is to manage access to the network. IEEE802.11 are …


Small-Separation Speckle Contrast Optical Spectroscopy For Intraoperative Assessment Of Parathyroid Glands Viability During Thyroid Surgery, Connor Berger 2022 Kennesaw State University

Small-Separation Speckle Contrast Optical Spectroscopy For Intraoperative Assessment Of Parathyroid Glands Viability During Thyroid Surgery, Connor Berger

Symposium of Student Scholars

The parathyroid glands (PTGs) are often damaged during thyroid surgeries due to a lack of methods identifying PTGs and assessing their viability. Damage to PTGs can cause hypocalcemia, a deficiency of calcium in the body. This complication can lead to detrimental consequences with economic burden. The surgeon’s current method of viability assessment is qualitative and subjective. Our technical solution is to employ an optical technique called speckle contrast optical spectroscopy (SCOS) that noninvasively quantifies the blood flow index (Db) of biological tissues at deep tissue levels (>1cm). The goal of this project is to verify SCOS at small source-detector-separation …


Power System Transients: Impacts Of Non-Ideal Sensors On Measurement-Based Applications, Aaron Wilson 2022 University of Tennessee, Knoxville

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 …


Oam-Based Wavelets In A High Speed Optical Probing System For Measuring The Angular Decomposition Of The Environment, Justin Free 2022 Clemson University

Oam-Based Wavelets In A High Speed Optical Probing System For Measuring The Angular Decomposition Of The Environment, Justin Free

All Theses

This thesis presents the theoretical development of orbital angular momentum (OAM) based wavelets for the analysis of localized OAM information in space. An optical probing system for generating and detecting these wavelets is demonstrated; individual wavelets can scan the environment in 10µs or less. The probing system was applied to a three-dimensional atmospheric turbulence distribution to obtain a continuous wavelet transform of the angular information of the turbulent propagation path about a fixed radius. An entire continuous wavelet transform was measured in 3.8ms; the measurements are much faster than the turbulence and give insight into the short time scale of …


Design And Comparison Of Asynchronous Fft Implementations, Julie Bigot 2022 University of Arkansas, Fayetteville

Design And Comparison Of Asynchronous Fft Implementations, Julie Bigot

Graduate Theses and Dissertations

Fast Fourier Transform (FFT) is a widely used digital signal processing technology in a large variety of applications. For battery-powered embedded systems incorporating FFT, its physical implementation is constrained by strict power consumption, especially during idle periods. Compared to the prevailing clocked synchronous counterpart, quasi-delay insensitive asynchronous circuits offer a series of advantages including flexible timing requirement and lower leakage power, making them ideal choices for these systems. In this thesis work, various FFT configurations were implemented in the low-power Multi-Threshold NULL Convention Logic (MTNCL) paradigm. Analysis illustrates the area and power consumption trends along the changing of the number …


Low Power Multi-Channel Interface For Charge Based Tactile Sensors, Samuel Hansen 2022 University of Nebraska-Lincoln

Low Power Multi-Channel Interface For Charge Based Tactile Sensors, Samuel Hansen

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Analog front end electronics are designed in 65 nm CMOS technology to process charge pulses arriving from a tactile sensor array. This is accomplished through the use of charge sensitive amplifiers and discrete time filters with tunable clock signals located in each of the analog front ends. Sensors were emulated using Gaussian pulses during simulation. The digital side of the system uses SAR (successive approximation register) ADCs for sampling of the processed sensor signals.

Adviser: Sina Balkır


Denoising And Deconvolving Sperm Whale Data In The Northern Gulf Of Mexico Using Fourier And Wavelet Techniques, Kendal McCain Leftwich 2022 University of New Orleans, New Orleans

Denoising And Deconvolving Sperm Whale Data In The Northern Gulf Of Mexico Using Fourier And Wavelet Techniques, Kendal Mccain Leftwich

University of New Orleans Theses and Dissertations

The use of underwater acoustics can be an important component in obtaining information from the oceans of the world. It is desirable (but difficult) to compile an acoustic catalog of sounds emitted by various underwater objects to complement optical catalogs. For example, the current visual catalog for whale tail flukes of large marine mammals (whales) can identify even individual whales from their individual fluke characteristics. However, since sperm whales, Physeter microcephalus, do not fluke up when they dive, they cannot be identified in this manner. A corresponding acoustic catalog for sperm whale clicks could be compiled to identify individual …


A Statistical Analysis Of Sporadic-E Characteristics Associated With Gnss Radio Occultation Phase And Amplitude Scintillations, Daniel J. Emmons, Dong L. Wu, Nimalan Swarnalingam 2022 Air Force Institute of Technology

A Statistical Analysis Of Sporadic-E Characteristics Associated With Gnss Radio Occultation Phase And Amplitude Scintillations, Daniel J. Emmons, Dong L. Wu, Nimalan Swarnalingam

Faculty Publications

Statistical GNSS-RO measurements of phase and amplitude scintillation are analyzed at the mid-latitudes in the local summer for a 100 km altitude. These conditions are known to contain frequent sporadic-E, and the S4-σϕ trends provide insight into the statistical distributions of the sporadic-E parameters. Joint two-dimensional S4-σϕ histograms are presented, showing roughly linear trends until the S4 saturates near 0.8. To interpret the measurements and understand the sporadic-E contributions, 10,000 simulations of RO signals perturbed by sporadic-E layers are performed using length, intensity, and vertical thickness distributions from previous studies, with the assumption that the sporadic-E layer acts …


Digital Commons powered by bepress