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Filtering by: Creator Stock, David E. Remove constraint Creator: Stock, David E. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Channel Estimation in TDD MU-MIMO Systems using Sub-Linear Sparse Signal Recovery Algorithms

    Creator:
    Barry, David G.
    Abstract:
    Massive Multiple-User Miltiple-Input Multiple-Output (MU-MIMO) wireless communication systems incorporate promising advanced strong technologies for upcoming 5G communications. To obtain some of the high spectrum and energy e ciencies bonuses brought by MU-MIMO systems, the ability to obtain Channel State information, especially on the receiver side (CSI), is important. To minimize...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF David Barry for the degree of

  • Efficient Deep Learning Methods for Biomedical Applications

    Creator:
    Thota, Narayana Bhagirath
    Abstract:
    Deep Learning methods have been gaining a lot of significance for various Biomedical applications for diagnosing several types of diseases. Two applications considered here are: 1) Diabetic Retinopathy Detection and 2) ECG signal Classification (or Arrhythmia Detection). Diabetic Retinopathy (DR) is a major cause of blindness in Diabetic patients, and...
    Resource Type:
    Masters Thesis
    Full Text:
    approved: ______________________________________________________ David J. Allstot The diagnosis

  • Computational Approaches for RNA Structure Prediction with Dynamic Programming and Deep Neural Networks

    Creator:
    Deng, Dezhong
    Abstract:
    Our goal is to build a system to model the RNA sequences that reveals their structural information by using efficient dynamic programming algorithms and deep learning approaches. We aim to 1) achieve linear-time for RNA secondary structure prediction based on existing minimum free energy models; 2) utilize deep neural networks...
    Resource Type:
    Dissertation
    Full Text:
    Abstract approved: David A. Hendrix Our goal is to build a system to model the RNA sequences that reveals

  • Fabrication and characterization of thin-film transistor materials and devices

    Creator:
    Hong, David
    Abstract:
    A class of inorganic thin-film transistor (TFT) semiconductor materials has emerged involving oxides composed of post-transitional cations with (n-1)d¹⁰ns⁰ (n≥4) electronic configurations. This thesis is devoted to the pursuit of topics involving the development of these materials for TFT applications: Deposition of zinc oxide and zinc tin oxide semiconductor layers...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF David Hong for the degree of

  • Adaptive broadband wireless interference mitigation architecture applying higher order statistics algorithm for computer platform

    Creator:
    Wang, Qiwei
    Abstract:
    The broadband wireless interference in a computer platform is resulted by multiple electro-magnetic emission sources. This non-Gaussian interference is proved to be double-sided K-distributed in previous research. With the limitation of transmission power and dimension of the device, interference mitigation is an efficient way to improve received signal bit error...
    Resource Type:
    Masters Thesis
    Full Text:
    : _____________________________________________________ Mario E. Magaña The broadband wireless interference in a computer platform is resulted by

  • Deep ultraviolet solid-state laser development

    Creator:
    Dutton, David A. (David Adam)
    Abstract:
    There is a new possibility of generating deep ultraviolet laser radiation from a solid-state source. With recent advances in material development, a new nonlinear optical crystal provides a greater damage threshold than current materials making higher conversion efficiencies possible. This thesis examines the possibility of using this crystal to generate...
    Resource Type:
    Masters Thesis
    Full Text:
    THESIS OF David A. Dutton for the degree of Master of Science in Electrical and Computer

  • Transparent electronics : thin-film transistors and integrated circuits

    Creator:
    Presley, Rick E.
    Abstract:
    This thesis focuses on two aspects of transparent electronics, SnO₂ transparent thin-film transistors (TTFTs) and transparent circuits. Both depletion- and enhancement-mode SnO₂ TTFTs are realized. The maximum effective mobility for the depletion- and enhancement-mode devices are 2 cm²V⁻¹s⁻¹ and 0.8 cm²V⁻¹s⁻¹, respectively. A variety of techniques to decrease the carrier...
    Resource Type:
    Masters Thesis
    Full Text:
    thesis.dvi AN ABSTRACT OF THE THESIS OF Rick E. Presley for the degree

  • Machine Learning Methods for the Discovery and Analysis of MicroRNAs

    Creator:
    Bell, Jimmy D.
    Abstract:
    MicroRNAs are a highly conserved class of small endogenous RNA, about ~22nt in length, involved in post-transcriptional gene silencing and have prominent roles in disease and development. Though the process of microRNA discovery was once an arduous task, the advent of high throughput sequencing technology has resulted in novel microRNAs...
    Resource Type:
    Masters Thesis
    Full Text:
    : ______________________________________________________ David A. Hendrix MicroRNAs are a highly conserved class of small endogenous RNA, about

  • Deep Learning for Human and Biological Languages

    Creator:
    Hong, Junki
    Abstract:
    We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
    Resource Type:
    Dissertation
    Full Text:
    Human and Biological Languages Abstract approved: David Hendrix and Liang Huang We explore the

  • Interpretable Machine Learning: Applications in Biology and Genomics

    Creator:
    Danaee, Padideh
    Abstract:
    Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
    Resource Type:
    Dissertation
    Full Text:
    Machine Learning: Applications in Biology and Genomics Abstract approved: David A. Hendrix Machine