Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Title
Now showing items 213-232 of 1263
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Correlation-aware Splitting Algorithms for Opportunistic Selection
Opportunistic selection is a key technique to improve the performance of wireless systems. In it, the best set of users among the available ones is selected on the basis of their instantaneous channel gains or local ... -
Cost Effective Multi-role Active EMI Filters for Switched Mode Converters
Switched mode power converters are a major source of conducted electromagnetic interference (EMI). The popular technique for mitigation of conducted EMI uses EMI filters. EMI filters may be classified in two types based ... -
Coupling Of Electromagnetic Fields From Intentional High Power Electromagnetic Sources With A Buried Cable And An Airborne Vehicle In Flight
(2017-05-23)Society’s dependence on electronic and electrical systems has increased rapidly over the past few decades, and people are relying more and more on these gadgets in their daily life because of the efficiency in operation ... -
Cross-Modal Retrieval and Hashing
The objective of cross-modal retrieval is to retrieve relevant items from one modality (say image), given a query from another modality (say textual document). Cross-modal retrieval has various applications like matching ... -
Current-Mode Techniques In The Synthesis And Applications Of Analog And Multi-Valued Logic In Mixed Signal Design
(2008-10-07)The development of modern integration technologies is normally driven by the needs of digital CMOS circuit design. Rapid progress in silicon VLSI technologies has made it possible to implement multi-function and high ... -
Data Efficient Domain Generalization
Deep neural networks has brought tremendous success in many areas of computer vision, such as image classification, retrieval, segmentation , etc. However, this success is mostly measured under two conditions namely (1) ... -
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 ... -
Decentralized information flow control for the robot operating system
The Robot Operating System (ROS) is a popular open-source middleware widely used in the robotics community. While ROS provides extensive support for robotic application develop- ment, it lacks certain fundamental security ... -
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 Based Channel Estimation in Wireless Communications
Deep learning techniques which employ trained neural networks to solve problems have witnessed widespread adoption in diverse fields like medicine, architecture, robotics, autonomous vehicles, wireless communications, ... -
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, ...