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mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Trellis coded quantization
    sub title: an efficient technique for data compression
  name:
    name part: Marcellin, Michael Wesley.
    role:
      role term: creator
  name:
    name part: Fischer, Thomas
    role:
      role term: degree supervisor.
  name:
    name part: Cantrell, P. E.
    role:
      role term: degree committee member.
  name:
    name part: Dahm, P. F.
    role:
      role term: degree committee member.
  name:
    name part: Georghiades, C. N.
    role:
      role term: degree committee member.
  name:
    name part: Texas A & M University
    role:
      role term: degree granting institution.
  type of resource: text
  genre: bibliography
  genre: Academic theses
  origin info:
    place:
      place term: xx
    date issued: 1987
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: xiv, 116 leaves : illustrations ; 29 cm
  abstract: The ideas of signal set expansion and set partitioning from trellis coded modulation (TCM) are used to develop a new source coding technique which we call trellis coded quantization (TCQ). TCQ is theoretically justified by alphabet constrained rate distortion theory, which is an exact dual of the channel capacity argument used to justify TCM. The resulting structure is computationally efficient and achieves excellent performance for the memoryless uniform, Gaussian, and Laplacian sources. The effects of channel errors are examined and specific bounds are developed for the number of samples that can be affected by a single channel error. For the memoryless uniform source, TCQ achieves a mean squared error (MSE) within .21 dB of the distortion rate function at all positive integer encoding rates. This performance is superior to that of the best lattice quantizers known in up to 24 dimensions. For encoding the memoryless Gaussian source at encoding rates of 0.5, 1, and 2 bits per sample, TCQ outperforms all source coding schemes we have seen in the literature (including stochastic trellis coders and entropy coded quantization). The computational requirements of TCQ are quite modest. In the most important case, encoding a memoryless source at an encoding rate of R bits per sample using TCQ requires only 4 multiplies, 2N + 4 adds, N compares, and 4 rate-(R - 1) scalar quantizations per data sample, where N is the number of states in the encoding trellis. Trellis coded quantization is used as the basis of a predictive source coding scheme for Gauss-Markov sources and sampled speech. The performance for Gauss-Markov sources is quite good. Mean squared error within 1.3 dB of the distortion rate function is achieved at encoding rates of 1, 2, and 3 bits per sample for several Gauss-Markov sources used as models for sampled speech. Systems with fixed prediction/fixed residual encoding, fixed prediction/adaptive residual encoding, and adaptive prediction/adaptive residual enco…
  note: Typescript (photocopy).
  note: Vita.
  note: "Major subject: Electrical Engineering."
  note: Ph. D. Texas A & M University 1987
  note: Includes bibliographical references (leaves 92-95).
  subject:
    topic: Data compression (Telecommunication)
  subject:
    topic: Coding theory
  subject:
    topic: Signal processing
    topic: Digital techniques
  subject:
    topic: Major electrical engineering
  identifier: http://gateway.proquest.com/openurl
  identifier: http://proxy.library.tamu.edu/login
  related item:
    location:
      url: http://proxy.library.tamu.edu/login
  related item:
    location:
      url: http://gateway.proquest.com/openurl
  record info:
    record content source: TXA
    record creation date: 881206
    record change date: 20200904152410.0
    record identifier: in00000726432
    language of cataloging:
      language term: eng