Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Title
Now showing items 194-213 of 1130
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Data Fusion Based Physical Layer Protocols for Cognitive Radio Applications
(2017-09-26)This thesis proposes and analyzes data fusion algorithms that operate on the physical layer of a wireless sensor network, in the context of three applications of cognitive radios: 1. Cooperative spectrum sensing via binary ... -
Data Structures and Algorithms to Analyze Concurrency in Android Applications
Android is a popular mobile operating system, providing a rich ecosystem for the development of applications which run on the Android platform. Entities such as the device user, network and sensors interact continuously ... -
Dead-Time Induced Oscillations in Voltage Source Inverter-Fed Induction Motor Drives
(2017-12-07)The inverter dead-time is integral to the safety of a voltage source inverter (VSI). Dead-time is introduced between the complementary gating signals of the top and bottom switches in each VSI leg to prevent shoot-through ... -
Decision Making under Uncertainty : Reinforcement Learning Algorithms and Applications in Cloud Computing, Crowdsourcing and Predictive Analytics
In this thesis, we study both theoretical and practical aspects of decision making, with a focus on reinforcement learning based methods. Reinforcement learning (RL) is a form of semi-supervised learning in which the agent ... -
Deep Learning for Bug Localization and Program Repair
In this thesis, we focus on the problem of program debugging and present novel deep learning based techniques for bug-localization and program repair. Deep learning techniques have been successfully applied to a variety ... -
Deep Learning Methods For Audio EEG Analysis
The perception of speech and audio is one of the defining features of humans. Much of the brain’s underlying processes as we listen to acoustic signals are unknown, and significant research efforts are needed to unravel ... -
Deep Learning Models for Few-shot and Metric Learning
Deep neural network-based models have achieved unprecedented performance levels over many tasks in the traditional supervised setting and scale well with large quantities of data. On the other hand, improving performance ... -
Deep Learning over Hypergraphs
Graphs have been extensively used for modelling real-world network datasets, however, they are restricted to pairwise relationships, i.e., each edge connects exactly two vertices. Hypergraphs relax the notion of edges ... -
Deep Learning with Minimal Supervision
Abstract In recent years, deep neural networks have achieved extraordinary performance on supervised learning tasks. Convolutional neural networks (CNN) have vastly improved the state of the art for most computer vision ... -
Degradation Studies on Polymeric Insulators used for EHV and UHV Transmission
High voltage insulators used in overhead power transmission systems are of key im- portance for safe, reliable, and effcient operation of transmission line in transferring huge amount of electrical power. Conventionally, ... -
Delaunay Graphs for Various Geometric Objects
(2017-12-12)Given a set of n points P ⊂ R2, the Delaunay graph of P for a family of geometric objects C is a graph defined as follows: the vertex set is P and two points p, p' ∈ P are connected by an edge if and only if there exists ... -
Delay Differentiation By Balancing Weighted Queue Lengths
(2017-05-04)Scheduling policies adopted for statistical multiplexing should provide delay differentiation between different traffic classes, where each class represents an aggregate traffic of individual applications having same ... -
Delay Minimization of an M/M/1 Point-to-Point Link Model Subject to Throughput and Power Constraints
(2018-02-15)In this thesis, we address the problem of minimizing the average delay of data pack-ets served by a transmitter on a static, point-to-point link. The transmitter dynamically chooses state-dependent admission and transmission ... -
Demodulation of Narrowband Speech Spectrograms
(2017-11-22)Speech is a non-stationary signal and contains modulations in both spectral and temporal domains. Based on the type of modulations studied, most speech processing algorithms can be classified into short-time analysis ... -
Denoising and Refinement Methods for 3D Reconstruction
Capturing raw 3D data from the real world is the initial step for many 3D reconstruction pipelines in different computer vision applications. However, due to inaccuracies in measurement and oversimplification in mathematical ... -
DeNOx Studies In Diesel Exhaust Under AC/Pulse Energizations
(2015-11-16)It is the need of the hour to reduce the pollutants which poison our atmosphere and harm our health. The diesel engines are the most efficient IC engines in the world today, but paradoxically, they are also the engines ... -
Design & Implementation Of Low Power Sigma Delta ADCs For Wide Band Applications
(2013-06-13)This thesis focuses on the design and implementation of low power Σ∆ ADCs in 130 nanometer CMOS technology. The design issues in the implementation of a third order ADC with a multi-bit and single bit quantizer are discussed. ... -
Design and Analysis of a Re-Entrant Microwave Cavity and Its Application for a High-Performance Accelerometer
Accelerometers with high resolution are required for tracking and navigation in launch vehicles, spacecrafts, missiles and other strategic applications. Pendulous integrating gyroscopic accelerometer and force balanced ... -
Design and Analysis of Consistent Algorithms for Multiclass Learning Problems
(2018-08-14)We consider the broad framework of supervised learning, where one gets examples of objects together with some labels (such as tissue samples labeled as cancerous or non-cancerous, or images of handwritten digits labeled ...