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

Engineering Commons

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

Electrical and Computer Engineering

Deep learning

Graduate College Dissertations and Theses

Publication Year

Articles 1 - 2 of 2

Full-Text Articles in Engineering

Investigation Of Software Defined Radio And Deep Learning For Ground Penetrating Radar, Yan Zhang Jan 2024

Investigation Of Software Defined Radio And Deep Learning For Ground Penetrating Radar, Yan Zhang

Graduate College Dissertations and Theses

Ground Penetrating Radar (GPR) is a non-invasive geophysical method that uses radar pulses to image the subsurface. This technology is widely used to detect and map subsurface structures, utilities, and features without the need for physical excavation. Traditional GPR systems, which rely on fixed radio frequency electronics like Application-Specific Integrated Circuits (ASICs), have significant limitations in their flexibility and adaptability. Adjusting operational parameters such as waveform, frequency, and modulation schemes is challenging, which is crucial for tailoring performance to specific tasks or conditions. The considerable size and weight of these systems restrict their applicability in harsh or confined spaces where …


Intelligent Wide-Area Monitoring Systems Using Deep Learning, Mustafa Matar Jan 2023

Intelligent Wide-Area Monitoring Systems Using Deep Learning, Mustafa Matar

Graduate College Dissertations and Theses

Scientific advancements based on the wide-area measurements as a way to monitor systems, are fundamental in reliable operation of different types of complex networks. These advanced measurement units capable of real-time wide-area monitoring, which enables capture system dynamic behavior. Therefore, advanced technology is urgently necessary to analyze substantial streaming data from these networks and handle system uncertainties. As an example, uncertainties in power systems due to renewable energy and demand response. Power system operation, and planning have become more complex and vulnerable to extreme weather and natural disasters. Thus, increasing power system resilience has gained more attention.Machine Learning (ML), and …