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Filtering by: Creator Falconer, Lawrence L. Remove constraint Creator: Falconer, Lawrence L. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Modeling and analysis of spur structure of digital-to-time conversion based frequency synthesizers

    Creator:
    Talwalkar, Sumit A.
    Abstract:
    Frequency synthesizers are critical components of all communication systems. This thesis considers the issue of undesirable frequency spurs of a relatively recent type of frequency synthesis architecture called digital-to-time conversion (DTC). The DTC-based frequency synthesis architecture has important performance benefits over older frequency synthesizers, such as fast frequency switching, large...
    Resource Type:
    Dissertation
    Full Text:
    : S. Lawrence Marple, Jr. Frequency synthesizers are critical components of all communication

  • Multi-dimensional parametric estimation: two-dimensional sharpening by predictive bandwidth extrapolation and fast algorithms for three dimensional autoregressive estimation

    Creator:
    Liew, Ji Seok
    Abstract:
    Achieving sharpened (enhanced detail) features of a multi-dimensional data source using the linear prediction (LP) bandwidth extrapolation (BWE) technique in the transform domain is the main objective of this research. The evolution of sensor technology has provided acquisition scenarios in which the data format is inherently multi-dimensional, including hyperspectral imaging...
    Resource Type:
    Dissertation
    Full Text:
    Computer Engineering presented on June 6, 2006. Adviser: Dr. S. Lawrence Marple, Jr. Ji-Seok Liew

  • Enhanced inverse synthetic aperture radar imagery using 2-D spectral estimation

    Creator:
    Ohm, David R.
    Abstract:
    This research focused on the use of classical and modern two-dimensional spectral estimation techniques for enhancing inverse synthetic aperture radar (ISAR) imagery. 2-D Classical spectral estimation methods and 2-D modern parametric and non-parametric spectral estimation methods are applied to simulated and real data sets in order to achieve both range...
    Resource Type:
    Masters Thesis
    Full Text:
    . Lawrence Marple Jr. This research focused on the use of classical and modern two-dimensional spectral

  • Fast algorithms and applications for multi-dimensional least-squares-based minimum variance spectral estimation

    Creator:
    Wei, Lin
    Abstract:
    The main contributions of this thesis are the development and application of four computationally efficient solutions for least-squares-based (LS-based) minimum variance spectral estimation (MVSE). They are: (1) fast computational solution for the 1-D covariance LS-based MVSE, (2) fast computational solution for the 1-D modified covariance LS-based MVSE, (3) fast computational...
    Resource Type:
    Dissertation
    Full Text:
    Advisor: Dr. S. Lawrence Marple, Jr. AN ABSTRACT OF THE THESIS OF Lin Wei for the degree of Doctor

  • Kinematic and cyclostationary parameter estimation for co-channel emitter location applications

    Creator:
    Ohm, David R.
    Abstract:
    The problem of locating a signal source, or an emitter, has many civilian and military applications, such as communication regulations enforcement, military reconnaissance, and search-and-rescue operations. Many of the most widely used emitter location methods rely on the accurate and robust estimation of the differential time delay, or time-difference-of-arrival (TDOA),...
    Resource Type:
    Dissertation
    Full Text:
    Abstract approved: S. Lawrence Marple Jr. The problem of locating a signal source, or an emitter, has

  • Counterfactual States for Atari Agents via Generative Deep Learning

    Creator:
    Olson, Matthew L.
    Abstract:
    Although deep reinforcement learning agents have produced impressive results in many domains, their decision making is difficult to explain to humans. To address this problem, past work has mainly focused on explaining why an action was chosen in a given state. A different type of explanation that is useful is...
    Resource Type:
    Masters Thesis
    Full Text:
    acknowledge to my co-authors Lawrence Neal, Fuxin Li, and Weng-Keen Wong as without them this research would

  • Low power scheduling schemes that consider latency and resource constraints at multiple voltages

    Creator:
    Huang, Shyh-Sen
    Abstract:
    Power reduction can be achieved at many different levels, such as architecture, algorithm, logic, and transistor levels in circuit design. This thesis focuses on low power scheduling at the algorithm level. We present a latency-constrained scheduling and a latency and resource constrained scheduling, which minimize power consumption for the resources...
    Resource Type:
    Masters Thesis
    Full Text:
    5000 10000 15000 20000 25000 30000 1 1.2 1.5 1.8 2.2 2.4 3.3 5 Vo l tag e (v ) P o w er ( u

  • Communication-Efficient Secure Two-Party Computation From Minicrypt and OT

    Creator:
    Roy, Lawrence
    Abstract:
    Secure two-party computation (2PC) is the task of performing arbitrary calculations on secret inputs provided by two parties, while maintaining secrecy if at least one party is honest. 2PC has been applied to privacy-preserving record linkage and machine learning, in areas such as medicine where maintaining privacy is crucial. One...
    Resource Type:
    Dissertation
    Full Text:
    Computation From Minicrypt and OT AN ABSTRACT OF THE DISSERTATION OF Lawrence Roy for the degree of Doctor

  • Characterizing and Addressing Dataset Shift with Deep Learning

    Creator:
    Olson, Matthew L.
    Abstract:
    This dissertation delves into understanding, characterizing, and addressing dataset shift in deep learning, a pervasive issue for deployed machine learning systems. Integral aspects of the problem are examined: We start with the use of counterfactual explanations in order to characterize the behavior of deep reinforcement learning agents in visual input...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Matthew L

  • Applying machine learning for prediction, recommendation, and integration

    Creator:
    Bao, Xinlong
    Abstract:
    This dissertation explores the idea of applying machine learning technologies to help computer users find information and better organize electronic resources, by presenting the research work conducted in the following three applications: FolderPredictor, Stacking Recommendation Engines, and Integrating Learning and Reasoning. FolderPredictor is an intelligent desktop software tool that helps...
    Resource Type:
    Dissertation