• DocumentCode
    1226534
  • Title

    Minimum-variance deconvolution and maximum-likelihood deconvolution for nonwhite Bernoulli-Gaussian processes with a Joseph spectrum

  • Author

    Chi, Chong-Yung

  • Author_Institution
    Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu
  • Volume
    40
  • Issue
    3
  • fYear
    1992
  • fDate
    3/1/1992 12:00:00 AM
  • Firstpage
    676
  • Lastpage
    679
  • Abstract
    Todoeschuck and Jensen (1988) recently reported that the reflectivity sequences, denoted p(k), calculated from some sonic logs are not white and have a power spectral density approximately proportional to frequency, called a Joseph spectrum. It is shown here how to compute the minimum-variance estimate and maximum-likelihood estimate for a μ(k) modeled as a nonwhite Bernoulli-Gaussian (B-G) process with a Joseph spectrum. Also presented are the corresponding estimates for a statistically equivalent white B-G process μ*(k) which mimics μ(k). Some conclusions regarding the acceptability of these estimates are drawn
  • Keywords
    acoustic signal processing; random processes; spectral analysis; Joseph spectrum; maximum-likelihood deconvolution; minimum variance deconvolution; nonwhite Bernoulli-Gaussian processes; power spectral density; reflectivity sequences; sonic logs; white Bernoulli-Gaussian process; Biomedical acoustics; Biomedical measurements; Deconvolution; Frequency; Gaussian processes; Geology; Maximum likelihood estimation; Noise measurement; Seismic measurements; Signal processing algorithms;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.120810
  • Filename
    120810