• DocumentCode
    925170
  • Title

    Waveform-preserving blind estimation of multiple independent sources

  • Author

    Tong, Lang ; Inouye, Yujiro ; Liu, Ruey-wen

  • Author_Institution
    Dept. of Electr. & Comput. Eng., West Virginia Univ., Morgantown, WV, USA
  • Volume
    41
  • Issue
    7
  • fYear
    1993
  • fDate
    7/1/1993 12:00:00 AM
  • Firstpage
    2461
  • Lastpage
    2470
  • Abstract
    The problem of blind estimation of source signals is to estimate the source signals without knowing the characteristics of the transmission channel. It is shown that the minimum-variance unbiased estimates can be obtained if and only if the transmission channel can be identified blindly. It is shown that the channel can be blindly identified if and only if there is not more than one Gaussian source. This condition suggests that waveform-preserving blind estimation can be achieved over a wide range of signal processing applications, including those cases in which the source signals have identical nonGaussian distributions. The constructive proof of the necessary and sufficient condition serves as a foundation for the development of waveform-preserving blind signal estimation algorithms. Examples are presented to demonstrate the applications of the theoretical results
  • Keywords
    parameter estimation; signal processing; Gaussian source; blind channel identification; minimum-variance unbiased estimates; multiple independent sources; nonGaussian distributions; signal estimation algorithms; signal processing; transmission channel; waveform-preserving blind estimation; Array signal processing; Estimation; Gaussian distribution; Image restoration; Multiple signal classification; Sensor arrays; Signal processing; Signal processing algorithms; Signal restoration; Sufficient conditions;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.224254
  • Filename
    224254