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  • Feedback in multiple antenna wireless communication systems

    Creator:
    Xu, Tao
    Abstract:
    Multiple-input multiple-output wireless systems promise significant capacity gain and/or diversity gain over single antenna systems. If channel state information (CSI) is available at both the transmitter and the receiver, the performance can be further improved. In this thesis, first, we study binary index feedback problem in beamforming systems when the...
    Resource Type:
    Dissertation
    Full Text:
    disertation.dvi AN ABSTRACT OF THE THESIS OF Tao Xu for the

  • Low-power high-resolution delta-sigma ADC design techniques

    Creator:
    Wang, Tao
    Abstract:
    This dissertation presents a low-power high-resolution delta-sigma ADC. Two new architectural design techniques are proposed to reduce the power dissipation of the ADC. Compared to the conventional active adder, the direct charge transfer (DCT) adder greatly saves power by keeping the feedback factor of the active adder unity. However, the...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE THESIS OF Tao Wang for the degree of Doctor of Philosophy in Electrical and

  • Design techniques for successive approximation register analog-to-digital converters

    Creator:
    Tong, Tao
    Abstract:
    Successive approximation register analog-to-digital converters (SAR ADCs) have been widely used for medium-speed, medium-resolution applications due to their excellent power efficiency and digital compatibility. Recently, SAR ADCs are also penetrating into the applications which have been earlier dominated by delta-sigma ADCs and pipeline ADCs. However, the resolution of SAR ADCs...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Tao Tong for the degree of Master of Science in Electrical and

  • Design techniques for low-power multi-GS/s analog-to-digital converters

    Creator:
    Jiang, Tao
    Abstract:
    Ultra-high-speed (>10GS/s), medium-resolution (5~6bit), low-power (<50mW) analog-to-digital converter can find it application in the areas of digital oscilloscopes and next-generation serial link receivers. There are several challenges to enable a successful design, however. First, the time-interleaved architecture is required in order to achieve over 10GS/s sampling rate, with the trade-off...
    Resource Type:
    Dissertation
    Full Text:
    Kuo, Jiaming Lin, Jinzhou Cao, Tao Wang, Tao Tong, Xin Meng, and Wei Li in Professor Temes's group

  • Threshold Selection Based on the SNR in Time of Arrival Localization System

    Creator:
    Lyu, Tao
    Abstract:
    Threshold-based time of arrival (TOA) estimation is a technique for high-precision indoor localization. Existing threshold selection methods, such as xed thresh- old and normalized threshold methods, do not consider the signal-to-noise radio (SNR) value at the receiver. This is not desired for high-precision positioning. A proper threshold value depends on...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Tao Lyu for the degree of

  • The Partitioning Technique of Power System to Improve the Observability of Sub-System for Multi-area State Estimation

    Creator:
    Lyu, Tao
    Abstract:
    An accurate state estimation plays an essential role in power system operation and planning in energy management systems. However, existing multi-area state estimation researches have not focused on the importance of system clustering. The clustering mechanism divides or partitions a system according to user-defined criteria. Few published research works have...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Tao Lyu for the degree of

  • Toward Disentangling the Activations of the Deep Networks via Low-dimensional Embedding and Non-negative Factorization

    Creator:
    Khorram, Saeed
    Abstract:
    In this thesis, we introduce a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by embedding a high-dimensional activation vector of a deep network layer non-linearly into a low-dimensional explanation space while retaining faithfulness i.e., the original deep learning predictions can...
    Resource Type:
    Masters Thesis
    Full Text:
    Abstract approved: Fuxin Li In this thesis, we introduce a novel Explanation Neural Network (XNN) to

  • Visual object discovery and understanding

    Creator:
    Yuan, Jialin
    Abstract:
    Learning to recognize objects is a fundamental and essential step in human perception and understanding of the world. Accordingly, research of object discovery across diverse modalities plays a pivotal role in the context of computer vision. This field not only contributes significantly to enhancing our understanding of visual information but...
    Resource Type:
    Dissertation
    Full Text:
    : Visual Object Discovery and Understanding Abstract approved: Fuxin Li Learning to recognize objects is

  • Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression

    Creator:
    Wang, Xinyao
    Abstract:
    Heatmap regression has became one of the mainstream approaches to localize facial landmarks. As Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) are becoming popular in solving computer vision tasks, extensive research has been done on these architectures. However, the loss function for heatmap regression is rarely studied. In...
    Resource Type:
    Masters Thesis
    Full Text:
    for Robust Face Alignment via Heatmap Regression Abstract approved: Fuxin Li Heatmap regression has

  • Deep Convolutional Network on Point Clouds for 3D Scene Understanding

    Creator:
    Wu, Wenxuan
    Abstract:
    As one of the most popular data types, the point cloud is widely used in various appli- cations, including computer vision, computer graphics and robotics. The capability to directly measure 3D point clouds is invaluable in those applications as depth information could remove a lot of the segmentation ambiguities in...
    Resource Type:
    Dissertation
    Full Text:
    Convolutional Network on Point Clouds for 3D Scene Understanding Abstract approved: Fuxin Li As one of the