Signal Processing Commons^™

Design And Development Of Fiber Bragg Grating Sensor For Detecting Of Hydrogen Gas In Transformer Oil, Mohd Raffi Samsudin

Student Works (2020-2029)

Hermetically sealed oil-immersed transformers are the key to electricity distribution networks. They are also one of the most expensive facilities in the electricity supply network. Immediate replacement is expected for this type of transformer upon failure because it is directly connected to the customer. Transformer oil acts as insulation, coolant and condition indicator. To date, there is no economical real-time monitoring system available to monitor the transformer oil condition. Therefore, there is a need to develop a cheap, non-intrusive and non-electrical sensor to monitor the health of the transformer by measuring the amount of dissolved hydrogen gas in oil, which …

Ultra-Wideband Power Amplifier Design For Large Signal Application, Ragavan Krishnamoorthy

Student Works (2020-2029)

Broadband power amplifier design has become one of the most critical enabling block in today’s wireless communication technology. Numerous research efforts have been carried out throughout the years to establish high efficiency over wideband RF transmitter. This research work presents two approaches in achieving ultra-broadband power amplifier for RF transmitter. Firstly, a new technique for the design of ultra-broadband RF power amplifier is introduced, in which a combination of the reactance compensation and third-harmonic tuning are adopted. The design goal is to achieve 40 dBm (10W) output power across a wide frequency bandwidth operation. Theoretical design equations were developed to …

Anomalous Event Detection And Localization Based On Deep Generative Adversarial Networks For Surveillance Videos, Thittaporn Ganokratanaa

Chulalongkorn University Theses and Dissertations (Chula ETD)

Anomaly detection is of great significance for intelligent surveillance videos. Current works typically struggle with object detection and localization problems due to crowded scenes and lack of sufficient prior information of the objects of interest during training, resulting in false-positive detection results. Thus, in this thesis, we propose two novel frameworks for video anomaly detection and localization. We first propose a Deep Spatiotemporal Translation Network (DSTN), a novel unsupervised anomaly detection and localization method based on Generative Adversarial Network (GAN) and Edge Wrapping (EW). In this work, we introduce (i) a novel fusion of background removal and real optical flow …

Estimation Of Atmospheric Conditions Over A Long Horizontal Path Using Multi-Frame Blind Deconvolution (Mfbd) Techniques In Comparison With Delayed Tilt Anisoplanatism (Delta) Software, Hannah Stoll

Dissertations, Master's Theses and Master's Reports

The potential to track and view objects in space from the ground with greater near real time knowledge of the intervening turbulence would be a revolutionary capability. The objective of this thesis is to cross-validate two separate methods used to estimate the Fried parameter. This verification is a step toward a commercial grade product that would make real-time estimates of the turbulence strength along an optical path from a ground-based observatory to a satellite in orbit around the Earth. Michigan Technological University has developed a multi-frame blind deconvolution (MFBD) algorithm used to estimate r0 and it was tested against MZA’s …

Development Of A Software-Defined Underwater Acoustic Communication System, Zijian Zhu

Dissertations, Master's Theses and Master's Reports

This report started with a brief history and recent development of underwater acoustic communication systems as well as software-defined radio technologies. Then, some challenges from underwater acoustic channels and available underwater acoustic communication modems are discussed. After finished introducing the basics of SDR and GNU Radio, a detailed description of implementing a software-defined acoustic communication system in GNU Radio are presented, along with some key concepts of the system.

Then, some hardware specifications are presented, following by detailed documentation on a software-defined acoustic communication system experiment with a host computer, a USRP, an acoustic hydrophone, and a hydrophone. At the …

Object Identification In Radar Imaging Via The Reciprocity Gap Method, Matthew Charnley, Aihua W. Wood

Faculty Publications

In this paper, we present an experimental method for locating and identifying objects in radar imaging, specifically problems that could arise in physical situations. The data for the forward problem are generated using a discretization of the Lippmann‐Schwinger equation, and the inverse problem of object location is solved using the reciprocity gap approach to the linear sampling method. The main new development in this paper is an exploration of determining the permittivity of the object from the back‐scattered data, utilizing another discretization of the Lippmann‐Schwinger equation.
Abstract © AGU.

Image Restoration Using Automatic Damaged Regions Detection And Machine Learning-Based Inpainting Technique, Chloe Martin-King

Computational and Data Sciences (PhD) Dissertations

In this dissertation we propose two novel image restoration schemes. The first pertains to automatic detection of damaged regions in old photographs and digital images of cracked paintings. In cases when inpainting mask generation cannot be completely automatic, our detection algorithm facilitates precise mask creation, particularly useful for images containing damage that is tedious to annotate or difficult to geometrically define. The main contribution of this dissertation is the development and utilization of a new inpainting technique, region hiding, to repair a single image by training a convolutional neural network on various transformations of that image. Region hiding is also …

Radio Direction Finding Using Pseudo-Doppler For Uav-Based Animal Tracking, Anup Karki

Masters Theses

Radio Direction Finding (RDF) is commonly used for low cost tracking and navigation systems. However, for a low cost application and mobility, the design constraints are highly limited. Pseudo Doppler (PD) can improve RDF capabilities without being cost prohibitive. This work entails the analysis of PD RDF and its potential use for Unmanned Aerial Vehicles (UAV) that are currently employed in wildlife research animal tracking. PD is based on the doppler effect or doppler shift. The doppler effect works like a frequency modulator that increases or decreases the observed frequency depending on whether a signal source is approaching or receding …

Visual Speech Recognition Using A 3d Convolutional Neural Network, Matthew Rochford

Master's Theses

Main stream automatic speech recognition (ASR) makes use of audio data to identify spoken words, however visual speech recognition (VSR) has recently been of increased interest to researchers. VSR is used when audio data is corrupted or missing entirely and also to further enhance the accuracy of audio-based ASR systems. In this research, we present both a framework for building 3D feature cubes of lip data from videos and a 3D convolutional neural network (CNN) architecture for performing classification on a dataset of 100 spoken words, recorded in an uncontrolled envi- ronment. Our 3D-CNN architecture achieves a testing accuracy of …

Average Speech Directivity, Samuel D. Bellows, Claire M. Pincock, Jennifer K. Whiting, Timothy W. Leishman

Directivity

Speech directivity describes the angular dependence of acoustic radiation from a talker’s mouth and nostrils and diffraction about his or her body and chair (if seated). It is an essential physical aspect of communication affecting sounds and signals in acoustical environments, audio, and telecommunication systems. Because high-resolution, spherically comprehensive measurements of live, phonetically balanced speech have been unavailable in the past, the authors have undertaken research to produce and share such data for simulations of acoustical environments, optimizations of microphone placements, speech studies, and other applications. The measurements included three male and three female talkers who repeated phonetically balanced passages …

Paper-Based Flexible Electrode Using Chemically-Modified Graphene And Functionalized Multiwalled Carbon Nanotube Composites For Electrophysiological Signal Sensing, Md Faruk Hossain, Jae Sang Heo, John Nelson, Insoo Kim

Bioelectrics Publications

Flexible paper-based physiological sensor electrodes were developed using chemically-modified graphene (CG) and carboxylic-functionalized multiwalled carbon nanotube composites (f@MWCNTs). A solvothermal process with additional treatment was conducted to synthesize CG and f@MWCNTs to make CG-f@MWCNT composites. The composite was sonicated in an appropriate solvent to make a uniform suspension, and then it was drop cast on a nylon membrane in a vacuum filter. A number of batches (0%~35% f@MWCNTs) were prepared to investigate the performance of the physical characteristics. The 25% f@MWCNT-loaded composite showed the best adhesion on the paper substrate. The surface topography and chemical bonding of the proposed CG-f@MWCNT …

Demonstration Of Visible And Near Infrared Raman Spectrometers And Improved Matched Filter Model For Analysis Of Combined Raman Signals, Alexander Matthew Atkinson

Electrical & Computer Engineering Theses & Dissertations

Raman spectroscopy is a powerful analysis technique that has found applications in fields such as analytical chemistry, planetary sciences, and medical diagnostics. Recent studies have shown that analysis of Raman spectral profiles can be greatly assisted by use of computational models with achievements including high accuracy pure sample classification with imbalanced data sets and detection of ideal sample deviations for pharmaceutical quality control. The adoption of automated methods is a necessary step in streamlining the analysis process as Raman hardware becomes more advanced. Due to limits in the architectures of current machine learning based Raman classification models, transfer from pure …

Target Detection In Heterogeneous Clutter With Low Resolution Radar, Kyle G. Stankowski

Theses and Dissertations

This thesis develops a framework for SAR target detection and super-resolution in low-resolution environments. The primary focus in this research is the background clutter heterogeneity that often accompanies low range and cross-range resolutions. A corrective model which accounts for clutter replacement is developed to define the detection and false alarm rates of the detector more accurately than a traditional model in which the radar return from the target supplements the existing clutter. In a heterogeneous clutter cell, the clutter replacement model leverages the different scattering distributions among the individual clutter types to generate a probability distribution function for the areas …

A Harmless Wireless Quantum Alternative To Cell Phones Based On Quantum Noise, Florentin Smarandache, Robert Neil Boyd, Victor Christianto

Branch Mathematics and Statistics Faculty and Staff Publications

In the meantime we know that 4G and 5G technologies cause many harms to human health. Therefore, here we submit a harmless wireless quantum alternative to cell phones. It is our hope that this alternative

Autonomous And Resilient Management Of All-Source Sensors For Navigation Assurance, Juan D. Jurado

Theses and Dissertations

All-source navigation has become increasingly relevant over the past decade with the development of viable alternative sensor technologies. However, as the number and type of sensors informing a system increases, so does the probability of corrupting the system with sensor modeling errors, signal interference, and undetected faults. Though the latter of these has been extensively researched, the majority of existing approaches have constrained faults to biases, and designed algorithms centered around the assumption of simultaneously redundant, synchronous sensors with valid measurement models, none of which are guaranteed for all-source systems. This research aims to provide all-source multi-sensor resiliency, assurance, and …

Digital Holography Efficiency Experiments For Tactical Applications, Douglas E. Thornton

Theses and Dissertations

Digital holography (DH) uses coherent detection and offers direct access to the complex-optical field to sense and correct image aberrations in low signal-to-noise environments, which is critical for tactical applications. The performance of DH is compared to a similar, well studied deep-turbulence wavefront sensor, the self-referencing interferometer (SRI), with known efficiency losses. Wave optics simulations with deep-turbulence conditions and noise were conducted and the results show that DH outperforms the SRI by 10's of dB due to DH's strong reference. Additionally, efficiency experiments were conducted to investigate DH system losses. The experimental results show that the mixing efficiency (37%) is …

System And Method For Radio Tomographic Image Formation, Richard K. Martin

AFIT Patents

A system and method for generating radio tomographic images is provided. A plurality of transceivers positioned around a region to be imaged is divided into a plurality of pixels. A control apparatus is configured to cause each of the plurality of transceivers in turn to send a signal to each of the other transceivers. The control apparatus is further configured to determine an attenuation in the received signals, generate weighing, derivative, and attenuation matrices from the signals, group the pixels into a plurality of provinces, select each province in turn and solve for a change in attenuation in each of …

Gaussian Conditionally Markov Sequences: Theory With Application, Reza Rezaie

LSU New Orleans Theses and Dissertations

Markov processes have been widely studied and used for modeling problems. A Markov process has two main components (i.e., an evolution law and an initial distribution). Markov processes are not suitable for modeling some problems, for example, the problem of predicting a trajectory with a known destination. Such a problem has three main components: an origin, an evolution law, and a destination. The conditionally Markov (CM) process is a powerful mathematical tool for generalizing the Markov process. One class of CM processes, called $CM_L$, fits the above components of trajectories with a destination. The CM process combines the Markov property …

Interchangeable All Fiber-Based Passive Voa/Voc System, Andrei Statchevschi

Publications and Research

A passive interchangeable variable optical coupler and attenuator system is demonstrated. A maximum coupling ratio of 99.94/0.06 and attenuation of up to 30 dB were achieved respectively.

Re-Annotation Of Cough Events In The Ami Corpus, Paul Leamy, Damon Berry, David Dorran, Ted Burke

Conference papers

Cough sounds act as an important indicator of an individual's physical health, often used by medical professionals in diagnosing a patient's ailments. In recent years progress has been made in the area of automatically detecting cough events and, in certain cases, automatically identifying the ailment associated with a particular cough sound. Ethical and sensitivity issues associated with audio recordings of coughs makes it more difficult for this data to be made publicly available. However, without the public availability of a reliable database of cough sounds, developments in the area of audio event detection are likely to be hampered. The purpose …