• DocumentCode
    919093
  • Title

    Sampling and exact reconstruction of bandlimited signals with additive shot noise

  • Author

    Marziliano, Pina ; Vetterli, Martin ; Blu, Thierry

  • Author_Institution
    Lab. for Audio Visual Commun., Swiss Fed. Inst. of Technol., Lausanne, Switzerland
  • Volume
    52
  • Issue
    5
  • fYear
    2006
  • fDate
    5/1/2006 12:00:00 AM
  • Firstpage
    2230
  • Lastpage
    2233
  • Abstract
    In this correspondence, we consider sampling continuous-time periodic bandlimited signals which contain additive shot noise. The classical sampling scheme does not perfectly recover these particular nonbandlimited signals but only reconstructs a lowpass filtered approximation. By modeling the shot noise as a stream of Dirac pulses, we first show that the sum of a bandlimited signal with a stream of Dirac pulses falls into the class of signals that contain a finite rate of innovation, that is, a finite number of degrees of freedom. Second, by taking into account the degrees of freedom of the bandlimited signal in the sampling and reconstruction scheme developed previously for streams of Dirac pulses, we derive a sampling and perfect reconstruction scheme for the bandlimited signal with additive shot noise.
  • Keywords
    approximation theory; bandlimited signals; filtering theory; low-pass filters; shot noise; signal reconstruction; signal sampling; Dirac pulse; additive shot noise; bandlimited signal reconstruction; continuous-time periodic signal sampling; lowpass filtered approximation; Additive noise; Channel capacity; Convolution; Convolutional codes; Error correction codes; Feedback; Jacobian matrices; Maximum likelihood decoding; Sampling methods; Viterbi algorithm; Annihilating filters; Dirac pulses; degrees of freedom; nonbandlimited; rate of innovation; sampling; shot noise;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2006.872844
  • Filename
    1624657