Now showing items 31-40 of 75
Robust Wireless Communications for Low Power Short Message Internet-of-Things Applications
(2023)
This dissertation focuses on robust wireless communication system designs for low power short message IoT applications, aiming to enhance the reliability of the trans- mission. IoT applications possess unique challenges ...
Input and State Estimation for Discrete-Time Linear Systems with Application to Target Tracking and Fault Detection
(2018)
This dissertation first presents a deterministic treatment of discrete-time input reconstruction and state estimation without assuming the existence of a full-rank Markov parameter. Algorithms based on the generalized ...
Variable Weight Kernel Density Estimation
(2017)
Nonparametric density estimation is a common and important task in many problems in machine learning. It consists in estimating a density function from available observations without making parametric assumptions on the ...
Quantitative Image Reconstruction Methods for Low Signal-To-Noise Ratio Emission Tomography
(2020)
Novel internal radionuclide therapies such as radioembolization (RE) with Y-90 loaded microspheres and targeted therapies labeled with Lu-177 offer a unique promise for personalized treatment of cancer because imaging-based ...
Towards Closing the Programmability-Efficiency Gap using Software-Defined Hardware
(2021)
The past decade has seen the breakdown of two important trends in the computing industry: Moore’s law, an observation that the number of transistors in a chip roughly doubles every eighteen months, and Dennard scaling, ...
Streaming Architectures for Medical Image Reconstruction
(2020)
Non-invasive imaging modalities have recently seen increased use in clinical diagnostic procedures. Unfortunately, emerging computational imaging techniques, such as those found in 3D ultrasound and iterative magnetic ...
Eliciting and Leveraging Input Diversity in Crowd-Powered Intelligent Systems
(2019)
Collecting high quality annotations plays a crucial role in supporting machine learning algorithms, and thus, the creation of intelligent systems. Over the past decade, crowdsourcing has become a widely adopted means of ...
Analysis and Actions on Graph Data.
(2016)
Graphs are commonly used for representing relations between entities and handling data processing in various research fields, especially in social, cyber and physical networks. Many data mining and inference tasks can be ...
Robust Algorithms for Low-Rank and Sparse Matrix Models
(2018)
Data in statistical signal processing problems is often inherently matrix-valued, and a natural first step in working with such data is to impose a model with structure that captures the distinctive features of the underlying ...
Toward Robust Multi-Agent Autonomous Underwater Inspection with Consistency and Global Optimality Guarantees
(2019)
Teams of autonomous robotic systems have the potential to have a dramatic positive effect on our society. In the underwater domain specifically, collaborative multi-agent autonomous systems have the potential to lead to ...