Division of Electrical, Electronics, and Computer Science (EECS): Recent submissions
Now showing items 201-220 of 1305
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Machine Learning for Decoding Imagined words and Altered State of Consciousness from EEG
In the first part of the thesis, the results of our studies on the classification of phonological categories in imagined words are presented. We have investigated whether there are any statistically significant differences ... -
Graph Neural Networks with Parallel Local Neighborhood Aggregations
Graph neural networks (GNNs) have become very popular for processing and analyzing graph-structured data in the last few years. Using message passing as their basic building blocks that aggregate information from neighborhoods, ... -
Topics on Safety and Security of Power Systems
In this thesis, we investigate some of the problems concerning the safety and security of power systems. Since the operational safety of the power system itself is a vast area of research, we choose to investigate the ... -
Hardware-based Device Identification for Systems with Commercially Off-the-shelf Components
The Identity of an electronic device is a fundamental property, that bootstraps several applications such as authentication and traceability. For the purpose of device identification, conventional methods generate a unique ... -
Tailoring excitonic complexes in layered materials
Layered transition metal dichalcogenides (TMDCs) host a variety of strongly bound exciton complexes that control the optical properties in these materials. Apart from spin and valley, layer index provides an additional ... -
Medium Index Contrast Guided Mode Resonant Structures for Photonic Applications in the Visible-Near Infrared Wavelength Regime
Guided mode resonant (GMR) structures are interesting from the point of view of enhanced light-matter interaction and find applications in sensing, filtering, and miniaturized photonic components. The Guided mode resonance ... -
Reinforcement Learning in Large and Structured Environments
In a reinforcement learning (RL) problem, a learner takes actions to control the state of an initially unknown environment so as to maximize the sum of the rewards he obtains. This has several applications in many practical ... -
OTFS Modulation in MIMO Visible Light Communication Systems
Visible light communication (VLC) technology is emerging as an attractive technology for wireless communication in indoor and vehicular environments. In VLS systems, light emitting diodes (LED) and photo diodes (PD) ... -
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 ... -
Variational Bayes Algorithms for mmWave and Massive MIMO-OFDM Systems with Low Resolution ADCs
In this thesis, we develop novel low-complexity algorithms for massive multiple-input multiple-output (MIMO) systems under practical non-idealities and theoretically analyze their performance. The first problem we consider ... -
Modeling of Permittivity Variations in Stochastic Computational Electromagnetics
With the evolution of 5G systems offering high data rates, major changes are required in the design approach of the components of communication systems. Furthermore, building complex electromagnetic systems at the terahertz ... -
Addressing the Performance and Reliability Bottlenecks in 2D Transition Metal Dichalcogenide (TMD) Based Transistor Technology
In this thesis, we presented different contributions towards the development of 2D material technology. Firstly the realization of desired dimensions over singlecrystal high-quality MoS2 material through dry etching ... -
Algorithms for Fair Clustering
Many decisions today are taken by various machine learning algorithms, hence it is crucial to accommodate fairness in such algorithms to remove/reduce any kind of bias in the decision. We incorporate fairness in the ... -
Excitons in monolayer transition metal dichalcogenides
Excitons are quasiparticles formed due to electrostatic attraction between the electrons and the holes in a semiconductor. This Coulomb attraction is very strong in the mono- layers of Transition Metal Dichalcogenides ... -
Investigations on Polygonal Voltage Space Vector Structure generation with lower order harmonic suppression using switched capacitive filter throughout modulation range for Drive Applications
Multilevel inverters (MLI) are widely used in a host of industrial applications ranging from renewable energy systems, to electric vehicles, to distributed generation. Due to the switching nature of the output voltage, MLI ... -
2-Level Page Tables (2-LPT): A Building Block for Efficient Address Translation in Virtualized Environments
Efficient address translation mechanisms are gaining more and more attention as the virtual address range of the processors keeps expanding and the demand for machine virtualization increases with cloud and data center-based ... -
Nature-inspired Algorithms for Automated Deployment of Outdoor IoT Networks
A vast majority of the Internet of Things (IoT) devices will be connected in a topology where the edge-devices push data to a local gateway, which forwards the data to a cloud for further processing. In sizeable outdoor ... -
Novel First-order Algorithms for Non-smooth Optimization Problems in Machine Learning
This thesis is devoted to designing efficient optimization algorithms for machine learning (ML) problems where the underlying objective function to be optimized is convex but not necessarily differentiable. Such non-smooth ... -
Efficient Hardware Architectures for Error Correcting Codes Applicable to Data Storage
Error correcting codes (ECCs) are essential to transmission and data storage sys-tems to protect the information from errors introduced by noisy communication channels. There are two main classes of ECCs, namely algebraic ... -
Reinforcement Learning Algorithms for Off-Policy, Multi-Agent Learning and Applications to Smart Grids
Reinforcement Learning (RL) algorithms are a popular class of algorithms for training an agent to learn desired behavior through interaction with an environment whose dynamics is unknown to the agent. RL algorithms ...