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Compressed sensing (CS) is a novel approach to collecting and analyzing data of all types. By exploiting prior knowledge of the compressibility of many naturally-occurring signals, specially designed sensors

Compressed sensing (CS) is a novel approach to collecting and analyzing data of all types. By exploiting prior knowledge of the compressibility of many naturally-occurring signals, specially designed sensors can dramatically undersample the data of interest and still achieve high performance. However, the generated data are pseudorandomly mixed and must be processed before use. In this work, a model of a single-pixel compressive video camera is used to explore the problems of performing inference based on these undersampled measurements.

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    Date Created
    • 2016
    Resource Type
  • Text
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    Note
    • Partial requirement for: Ph.D., Arizona State University, 2016
      Note type
      thesis
    • Includes bibliographical references (pages 100-108)
      Note type
      bibliography
    • Field of study: Electrical engineering

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    by Henry Carlton Braun

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