Signal Processing Commons^™

Research Of Three-Phases Current’S Transducers Of Filter-Compensation Devices For Control Reactive Power’S Consumption Of Asynchronous Motor, Ilkhomjon Khakimovich Siddikov, Dilyorbek Karimjonov Doniyorbek O'G'Li -, Abdumutal Abdikarimovich Abdigapirov

Chemical Technology, Control and Management

In the article given materials of developing of three-phase electromagnetic current transducers of reactive power, using with asynchronous motor, methods connecting of two sensing element, series, parallel and differential and loops suitable for each phase, dynamic characteristics of output signals of three-phase electromagnetic current transducers asynchronous motor.

On the basis of modern calculation and design complexes are of great importance in the research variable sizes of three-phase current electromagnetic transducers of filter-compensation devices of reactive power of asynchronous motors. Presented mathematical model of research of electrical, electromagnetic and magnetic elements of electromagnetic current transducers in the …

On Refinements To Qmfd Based Chirp Parameter Estimation, Balu Santhanam, Thalanayar Santhanam

Electrical & Computer Engineering Technical Reports

Commuting matrix methods furnish a full basis of orthog- onal eigenvectors for the discrete Fourier transform or its centered version needed for computing the discrete fractional Fourier transform and multicomponent chirp signal analysis. However, these approaches suffer from ill-conditioning issues at higher matrix sizes, and require a computationally expensive eigenvalue decomposition.

In this paper, ill-conditioning issues associated with the QMFD approach developed previously by the authors are addressed via diagonal modification. Further symmetries of the eigenvectors are used to reduce the size of the underlying eigenvalue problem. These modifications are then incorporated into the real-arithmetic implementation of the QMFD approach …

An Epileptic Seizure Detection Method From Eeg Signals Based On A Classifier-Driven Feature Reduction Technique, Raymond N. Kamel

Theses and Dissertations

Epileptic seizure detection can improve the quality of life of epileptic patients, allow for more accurate medication, and minimize the risk of sudden unexpected death in epilepsy (SUDEP). This thesis work aims to develop a robust and stable algorithm for epileptic seizure detection through the classification of EEG signals. To achieve this aim, a methodology is proposed to develop a classifier that can differentiate between the healthy (normal), interictal, and ictal states of EEG signals, while maximizing the classification accuracy and minimizing the computational redundancy. The main pillar upon which this methodology is designed is using a problem-specific classifier-driven feature …

Editorial, Sameeh Ullah Dr.

International Journal of Smart Sensor and Adhoc Network

This special issue seeks papers that provide a convergent research perspective on business futures, i.e., research that draws on many disciplinary views and strives to establish fresh integrative frameworks and vocabularies. Addressing the difficulty of work culture and intelligent machines in a broad sense necessitates grappling with complicated issues such as motivation, cognition, machine learning, human learning, and system design, among others.

Live-Sky Gnss Signal Processing Using A Dual-Polarized Antenna Array For Multipath Mitigation, Eric Hahn, Sanjeev Gunawardena, Chris Bartone

Faculty Publications

Excerpt: Multipath results from reflections of Global navigation satellite signals (GNSS) signals arriving at a receiver that are delayed with respect to the desired line-of-sight (LOS) signals. The delayed signals distort the received LOS signals, thereby causing pseudorange and carrier phase measurement errors. Traditional multipath mitigation techniques include antenna gain pattern shaping (primarily to reduce ground multipath) and correlator gating techniques (such as narrow correlator and double-delta correlator [1]).

Accelerating A Software Defined Satnav Receiver Using Multiple Parallel Processing Schemes, Logan Reich, Sanjeev Gunawardena, Michael Braasch

Faculty Publications

Excerpt: Satnav SDRs present many benefits in terms of flexibility and configurability. However, due to the high bandwidth signals involved in satnav SDR processing, the software must be highly optimized for the host platform in order to achieve acceptable runtimes. Modules such as sample decoding, carrier replica generation, carrier wipeoff, and correlation are computationally intensive components that benefit from accelerations.

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 …

Context-Aware Collaborative Neuro-Symbolic Inference In Internet Of Battlefield Things, Tarek Abdelzaher, Nathaniel D. Bastian, Susmit Jha, Lance Kaplan, Mani Srivastava, Venugopal Veeravalli

ACI Journal Articles

IoBTs must feature collaborative, context-aware, multi-modal fusion for real-time, robust decision-making in adversarial environments. The integration of machine learning (ML) models into IoBTs has been successful at solving these problems at a small scale (e.g., AiTR), but state-of-the-art ML models grow exponentially with increasing temporal and spatial scale of modeled phenomena, and can thus become brittle, untrustworthy, and vulnerable when interpreting large-scale tactical edge data. To address this challenge, we need to develop principles and methodologies for uncertainty-quantified neuro-symbolic ML, where learning and inference exploit symbolic knowledge and reasoning, in addition to, multi-modal and multi-vantage sensor data. The approach features …

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 …

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

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-σ_ϕ trends provide insight into the statistical distributions of the sporadic-E parameters. Joint two-dimensional S4-σ_ϕ 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 …

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

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

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

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

Rdlnn-Based Image Forgery Detection And Forged Region Detection Using Mot, Akram Hatem Saber, Mohd Ayyub Khan, Basim Galeb Mejbel

Karbala International Journal of Modern Science

Image forgery detection TEMPhas become an emerging research area due to the increasing number of forged images circulating on the internet and other social media, which leads to legal and social issues. Image forgery detection includes the classification of an image as forged or authentic and as well as localizing the forgery wifin the image. In this paper, we propose a Regression Deep Learning Neural Network (RDLNN) based image forgery detection followed by Modified Otsu Thresholding (MOT) algorithm to detect the forged region. The proposed model comprises five steps that are preprocessing, image decomposition, feature extraction, classification and block matching. …

Long-Distance Propagation Of 162 Mhz Shipping Information Links Associated With Sporadic E, Alex T. Chartier, Thomas R. Hanley, Daniel J. Emmons

Faculty Publications

This is a study of anomalous long-distance (>1000 km) radio propagation that was identified in United States Coast Guard monitors of automatic identification system (AIS) shipping transmissions at 162 MHz. Our results indicate this long-distance propagation is caused by dense sporadic E layers in the daytime ionosphere, which were observed by nearby ionosondes at the same time. This finding is surprising because it indicates these sporadic E layers may be far more dense than previously thought.

Iris Detection Authenticator, Nathan D. Tang, Bryan K. Chau

Electrical Engineering

The development of iris biometric identification recognition is presented. Iris recognition differs from other methods because data acquisition is non-physical and is more accessible. It has been proven that the iris does not change as an individual ages and is well protected from external damages due to the eyelid and cornea, acting as a shield to the iris. In addition, the iris is almost impossible to forge due to its complex patterns and the current limitations in technology. Using Canny Edge Detection, Hough Transform, rubber-sheet normalization, Histogram of Gradient feature extraction, and the MultiMedia University iris database as our subjects, …

Device Free Indoor Localization Of Human Target Using Wifi Fingerprinting, Prasanga Neupane

LSU Master's Theses

Indoor localization of human objects has many important applications nowadays. Proposed here is a new device free approach where all the transceiver devices are fixed in an indoor environment so that the human target doesn't need to carry any transceiver device with them. This work proposes radio-frequency fingerprinting for the localization of human targets which makes this even more convenient as radio-frequency wireless signals can be easily acquired using an existing wireless network in an indoor environment. This work explores different avenues for optimal and effective placement of transmitter devices for better localization. In this work, an experimental environment is …

Hyperspectral Unmixing: A Theoretical Aspect And Applications To Crism Data Processing, Yuki Itoh

Doctoral Dissertations

Hyperspectral imaging has been deployed in earth and planetary remote sensing, and has contributed the development of new methods for monitoring the earth environment and new discoveries in planetary science. It has given scientists and engineers a new way to observe the surface of earth and planetary bodies by measuring the spectroscopic spectrum at a pixel scale.

Hyperspectal images require complex processing before practical use. One of the important goals of hyperspectral imaging is to obtain the images of reflectance spectrum. A raw image obtained by hyperspectral remote sensing usually undergoes conversion to a physical quantity representing the intensity of …

Predicting Insulin Pump Therapy Settings, Riccardo L. Ferraro, David Grijalva, Alex Trahan

SMU Data Science Review

Millions of people live with diabetes worldwide [7]. To mitigate some of the many symptoms associated with diabetes, an estimated 350,000 people in the United States rely on insulin pumps [17]. For many of these people, how effectively their insulin pump performs is the difference between sleeping through the night and a life threatening emergency treatment at a hospital. Three programmed insulin pump therapy settings governing effective insulin pump function are: Basal Rate (BR), Insulin Sensitivity Factor (ISF), and Carbohydrate Ratio (ICR). For many people using insulin pumps, these therapy settings are often not correct, given their physiological needs. While …