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ASU Electronic Theses and Dissertations


This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.


Subject
Date Range
2011 2019


The non-quasi-static (NQS) description of device behavior is useful in fast switching and high frequency circuit applications. Hence, it is necessary to develop a fast and accurate compact NQS model for both large-signal and small-signal simulations. A new relaxation-time-approximation based NQS MOSFET model, consistent between transient and small-signal simulations, has been developed for surface-potential-based MOSFET compact models. The new model is valid for all regions of operation and is compatible with, and at low frequencies recovers, the quasi-static (QS) description of the MOSFET. The model is implemented in two widely used circuit simulators and tested for speed and convergence. It …

Contributors
Zhu, Zeqin, Gildenblat, Gennady, Bakkaloglu, Bertan, et al.
Created Date
2012

Traditional wireless communication systems operate in duplexed modes i.e. using time division duplexing or frequency division duplexing. These methods can respectively emulate full duplex mode operation or realize full duplex mode operation with decreased spectral efficiency. This thesis presents a novel method of achieving full duplex operation by actively cancelling out the transmitted signal in pseudo-real time. With appropriate hardware, the algorithms and techniques used in this work can be implemented in real time without any knowledge of the channel or any training sequence. Convergence times of down to 1 ms can be achieved which is adequate for the coherence …

Contributors
Avasarala, Sanjay, Kiaei, Sayfe, Kitchen, Jennifer, et al.
Created Date
2016

Advances in miniaturized sensors and wireless technologies have enabled mobile health systems for efficient healthcare. A mobile health system assists the physician to monitor the patient's progress remotely and provide quick feedbacks and suggestions in case of emergencies, which reduces the cost of healthcare without the expense of hospitalization. This work involves development of an innovative mobile health system with adaptive biofeedback mechanism and demonstrates the importance of biofeedback in accurate measurements of physiological parameters to facilitate the diagnosis in mobile health systems. Resting Metabolic Rate (RMR) assessment, a key aspect in the treatment of diet related health problems is …

Contributors
Krishnan, Ranganath, Tao, Nongjian, Forzani, Erica, et al.
Created Date
2012

A signal with time-varying frequency content can often be expressed more clearly using a time-frequency representation (TFR), which maps the signal into a two-dimensional function of time and frequency, similar to musical notation. The thesis reviews one of the most commonly used TFRs, the Wigner distribution (WD), and discusses its application in Fourier optics: it is shown that the WD is analogous to the spectral dispersion that results from a diffraction grating, and time and frequency are similarly analogous to a one dimensional spatial coordinate and wavenumber. The grating is compared with a simple polychromator, which is a bank of …

Contributors
Weber, Peter Christian, Papandreou-Suppappola, Antonia, Tepedelenlioglu, Cihan, et al.
Created Date
2012

Immunosignaturing is a medical test for assessing the health status of a patient by applying microarrays of random sequence peptides to determine the patient's immune fingerprint by associating antibodies from a biological sample to immune responses. The immunosignature measurements can potentially provide pre-symptomatic diagnosis for infectious diseases or detection of biological threats. Currently, traditional bioinformatics tools, such as data mining classification algorithms, are used to process the large amount of peptide microarray data. However, these methods generally require training data and do not adapt to changing immune conditions or additional patient information. This work proposes advanced processing techniques to improve …

Contributors
Malin, Anna, Papandreou-Suppappola, Antonia, Bliss, Daniel, et al.
Created Date
2013

Parkinson's disease is a neurodegenerative condition diagnosed on patients with clinical history and motor signs of tremor, rigidity and bradykinesia, and the estimated number of patients living with Parkinson's disease around the world is seven to ten million. Deep brain stimulation (DBS) provides substantial relief of the motor signs of Parkinson's disease patients. It is an advanced surgical technique that is used when drug therapy is no longer sufficient for Parkinson's disease patients. DBS alleviates the motor symptoms of Parkinson's disease by targeting the subthalamic nucleus using high-frequency electrical stimulation. This work proposes a behavior recognition model for patients with …

Contributors
Dutta, Arindam, Papandreou-Suppappola, Antonia, Holbert, Keith E., et al.
Created Date
2015

Non-line-of-sight (NLOS) imaging of objects not visible to either the camera or illumina- tion source is a challenging task with vital applications including surveillance and robotics. Recent NLOS reconstruction advances have been achieved using time-resolved measure- ments. Acquiring these time-resolved measurements requires expensive and specialized detectors and laser sources. In work proposes a data-driven approach for NLOS 3D local- ization requiring only a conventional camera and projector. The localisation is performed using a voxelisation and a regression problem. Accuracy of greater than 90% is achieved in localizing a NLOS object to a 5cm × 5cm × 5cm volume in real …

Contributors
Chandran, Sreenithy, Jayasuriya, Suren, Turaga, Pavan, et al.
Created Date
2019

Structural integrity is an important characteristic of performance for critical components used in applications such as aeronautics, materials, construction and transportation. When appraising the structural integrity of these components, evaluation methods must be accurate. In addition to possessing capability to perform damage detection, the ability to monitor the level of damage over time can provide extremely useful information in assessing the operational worthiness of a structure and in determining whether the structure should be repaired or removed from service. In this work, a sequential Bayesian approach with active sensing is employed for monitoring crack growth within fatigue-loaded materials. The monitoring …

Contributors
Huff, Daniel William, Papandreou-Suppappola, Antonia, Kovvali, Narayan, et al.
Created Date
2013

Adaptive processing and classification of electrocardiogram (ECG) signals are important in eliminating the strenuous process of manually annotating ECG recordings for clinical use. Such algorithms require robust models whose parameters can adequately describe the ECG signals. Although different dynamic statistical models describing ECG signals currently exist, they depend considerably on a priori information and user-specified model parameters. Also, ECG beat morphologies, which vary greatly across patients and disease states, cannot be uniquely characterized by a single model. In this work, sequential Bayesian based methods are used to appropriately model and adaptively select the corresponding model parameters of ECG signals. An …

Contributors
Edla, Shwetha Reddy, Papandreou-Suppappola, Antonia, Chakrabarti, Chaitali, et al.
Created Date
2012

Presently, hard-switching buck/boost converters are dominantly used for automotive applications. Automotive applications have stringent system requirements for dc-dc converters, such as wide input voltage range and limited EMI noise emission. High switching frequency of the dc-dc converters is much desired in automotive applications for avoiding AM band interference and for compact size. However, hard switching buck converter is not suitable at high frequency operation because of its low efficiency. In addition, buck converter has high EMI noise due to its hard-switching. Therefore, soft-switching topologies are considered in this thesis work to improve the performance of the dc-dc converters. Many soft-switching …

Contributors
Nan, Chenhao, Ayyanar, Raja, Bakkaloglu, Bertan, et al.
Created Date
2016