Index Catalog // Hyrax

An inner product on adelic measures

Schöpfer:: Oberly, Peter J.
Abstract:: We define an inner product on a vector space of adelic measures over a number field $K$. We find that the norm induced by this inner product governs weak convergence at each place of $K$. The canonical adelic measure associated to a rational map is in this vector space, and...
Resource Type:: Dissertation

Convergence Analysis Framework for Fixed-Point Algorithms in Machine Learning and Signal Processing

Schöpfer:: Vu, Trung
Abstract:: Iterative algorithms are simple yet efficient in solving large-scale optimization problems in practice. With a surge in the amount of data in past decades, these methods have become increasingly important in many application areas including matrix/tensor recovery, deep learning, data mining, and reinforcement learning. To optimize or improve iterative algorithms,...
Resource Type:: Dissertation

A Rapid β-/γ Autoradiographic Imaging Method for Post-detonation Nuclear Forensics and Radiological Emergency Response

Schöpfer:: Foley, Ari A. R.
Abstract:: In a radiological emergency scenario, the capability to rapidly visualize radiation emitted from debris, contamination, or absorbed in biological samples, while visualizing the non-radioactive (or “conventional” image) features within a ﬁeld of view, will provide critical information to support optimization of further analysis, sample collection, and decision making. This research...
Resource Type:: Dissertation

Deletions and Insertions of the Symbol 0 and Asymmetric/Unidirectional Error Control Codes for the L₁ Metric

Schöpfer:: Alqwaifly, Nawaf
Abstract:: This work gives some theory and efficient design of binary block codes capable of controlling the deletions of the symbol “0” (referred to as 0-deletions) and/or the insertions of the symbol “0” (referred to as 0-insertions). This problem of controlling 0-deletions and/or 0-insertions (referred to as symmetric 0-errors) is shown...
Resource Type:: Dissertation

Predicting and Improving Throughput, Responsiveness and Battery Life of Computer Systems by Machine Learning

Schöpfer:: Li, Yunfan
Abstract:: The Machine Learning (ML) algorithms are increasingly explored in varies of fields including designing and optimizing computer systems. Recent research, such as optimizing memory/cache prefetching by ML training or predicting traffic pattern in throughput processors, also exhibits a promising future of introducing ML into computer system design and optimization. Throughput...
Resource Type:: Dissertation

Architecture Optimizations for Memory Systems of Throughput Processors

Schöpfer:: Gu, Yongbin
Abstract:: Throughput-oriented processors, such as graphics processing units (GPUs), have been increasingly used to accelerate general purpose computing, including machine learning models that are being utilized in numerous disciplines. Thousands of concurrently running threads in a GPU demand a highly efficient memory subsystem for data supply in GPUs. In this dissertation,...
Resource Type:: Dissertation

Identifiability-Aware Joint Sparse Error Correction For Robust State Estimation

Schöpfer:: Kibria, Sharmin
Abstract:: We study joint nonlinear state estimation with multi-period measurement vectors that are potentially corrupted by sparse gross errors. The identifiability-aware approach is proposed to leverage common characteristics of fundamentally identifiable gross errors to enhance error correction performance. First, we derive a necessary rank condition that the sparsity pattern of any...
Resource Type:: Dissertation

Adaptive Streaming Methods using Dual Protocols and Reinforcement Learning

Schöpfer:: Gatimu, Kevin
Abstract:: The ubiquity of high quality video and proliferation of mobile devices has contributed to an unprecedented rise in video consumption. HTTP, in conjunction with adaptive streaming, has become the de facto mechanism for delivering the vast majority of video as it readily caters to heterogeneous networks and devices. This dissertation...
Resource Type:: Dissertation

Co-channel Blocker and Self-Interferer Tolerant Receiver Architectures for MIMO and Full-Duplex MIMO Receivers

Schöpfer:: Jain, Sanket
Abstract:: This research focuses on receiver architectures which enable better spectral eciency by handling blockers in the same spectral range as the signal. The presence of such blockers, without the use of blocker cancelling/ltering techniques leads to gain compression and hence, consequent performance degradation of receivers leading to reduced spectrum...
Resource Type:: Dissertation

Dynamic and Dual Streaming Methods for H.264 Video and Parallel Performance Modeling

Schöpfer:: Johnson, Taylor N.
Abstract:: Traditional approaches to streaming H.264 video over a network typically rely on a single method of transport (i.e., reliable or unreliable) and/or use static values for parameters that can have a significant negative impact on the perceptual quality of the received video. This dissertation presents a dynamic method for wireless...
Resource Type:: Dissertation

Hyrax

An inner product on adelic measures

Convergence Analysis Framework for Fixed-Point Algorithms in Machine Learning and Signal Processing

A Rapid β-/γ Autoradiographic Imaging Method for Post-detonation Nuclear Forensics and Radiological Emergency Response

Deletions and Insertions of the Symbol 0 and Asymmetric/Unidirectional Error Control Codes for the L₁ Metric

Predicting and Improving Throughput, Responsiveness and Battery Life of Computer Systems by Machine Learning

Architecture Optimizations for Memory Systems of Throughput Processors

Identifiability-Aware Joint Sparse Error Correction For Robust State Estimation

Adaptive Streaming Methods using Dual Protocols and Reinforcement Learning

Co-channel Blocker and Self-Interferer Tolerant Receiver Architectures for MIMO and Full-Duplex MIMO Receivers

Dynamic and Dual Streaming Methods for H.264 Video and Parallel Performance Modeling

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