Отображение 1 - 10 результаты of 10 для поиска '"Random noise theory."', время запроса: 0.01сек. Отмена результатов
  1. 1

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

    Опубликовано 2016
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    A signal theoretic introduction to random processes
  2. 2

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

    Опубликовано 2004
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    An innovation approach to random fields application of white noise theory
  3. 3

    Noise trading and exchange rate regimes по Jeanne, Olivier

    Опубликовано 1999
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    Noise trading and exchange rate regimes
  4. 4

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

    Опубликовано 1997
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    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 по Brown, Robert Grover

    Опубликовано 1997
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    Introduction to random signals and applied filtering with MATLAB exercises and solutions
  6. 6

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

    Опубликовано 1995
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    Detection of signals in noise
  7. 7

    Signal detection theory по Hancock, John C.

    Опубликовано 1966
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    Signal detection theory
  8. 8

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

    Опубликовано 1965
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    Modulation, noise, and spectral analysis applied to information transmission
  9. 9

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

    Опубликовано 1965
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    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 по Soriano, Maricor Narvaez 1970-

    Диссертация

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

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