Résultat(s) 1 - 10 résultats de 10 pour la requête '"Random noise theory."', Temps de recherche: 0,01s Affiner les résultats
  1. 1

    A signal theoretic introduction to random processes par Howard, Roy M., author

    Publié 2016
    Livre

    A signal theoretic introduction to random processes
  2. 2

    An innovation approach to random fields application of white noise theory par Hida, Takeyuki 1927-

    Publié 2004
    Livre

    An innovation approach to random fields application of white noise theory
  3. 3

    Noise trading and exchange rate regimes par Jeanne, Olivier

    Publié 1999
    Livre

    Noise trading and exchange rate regimes
  4. 4

    Introduction to random signals and applied Kalman filtering with MATLAB exercises and solutions par Brown, Robert Grover

    Publié 1997
    Livre

    Introduction to random signals and applied Kalman filtering with MATLAB exercises and solutions
  5. 5

    Introduction to random signals and applied filtering with MATLAB exercises and solutions par Brown, Robert Grover

    Publié 1997
    Livre

    Introduction to random signals and applied filtering with MATLAB exercises and solutions
  6. 6

    Detection of signals in noise par McDonough, Robert N., Whalen, Anthony D.

    Publié 1995
    Livre

    Detection of signals in noise
  7. 7

    Signal detection theory par Hancock, John C.

    Publié 1966
    Livre

    Signal detection theory
  8. 8

    Modulation, noise, and spectral analysis applied to information transmission par Panter, Philip F.

    Publié 1965
    Livre

    Modulation, noise, and spectral analysis applied to information transmission
  9. 9

    Linear data-smoothing and prediction in theory and practice. par Blackman, Ralph Beebe 1904-

    Publié 1965
    Livre

    Linear data-smoothing and prediction in theory and practice.
  10. 10

    Improved classification of noisy microscopic images by a neural network with principal component projections as inputs par Soriano, Maricor Narvaez 1970-

    Thèse

    Improved classification of noisy microscopic images by a neural network with principal component projections as inputs

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