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  2. Pseudorandom noise - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_noise

    A pseudo-noise code (PN code) or pseudo-random-noise code (PRN code) is one that has a spectrum similar to a random sequence of bits but is deterministically generated. The most commonly used sequences in direct-sequence spread spectrum systems are maximal length sequences, Gold codes, Kasami codes, and Barker codes. [4]

  3. Autocorrelation - Wikipedia

    en.wikipedia.org/wiki/Autocorrelation

    Download QR code; Print/export ... of the autocorrelation as a correlation provides a scale-free measure of the strength of ... 1.3.4 Autocorrelation of white noise.

  4. Partial autocorrelation function - Wikipedia

    en.wikipedia.org/wiki/Partial_autocorrelation...

    White noise: The partial autocorrelation is 0 for all lags. Autoregressive model: The partial autocorrelation for an AR(p) model is nonzero for lags less than or equal to p and 0 for lags greater than p. Moving-average model: If , >, the partial autocorrelation oscillates to 0.

  5. White noise - Wikipedia

    en.wikipedia.org/wiki/White_noise

    White noise draws its name from white light, [2] although light that appears white generally does not have a flat power spectral density over the visible band. An image of salt-and-pepper noise In discrete time , white noise is a discrete signal whose samples are regarded as a sequence of serially uncorrelated random variables with zero mean ...

  6. Detrended fluctuation analysis - Wikipedia

    en.wikipedia.org/wiki/Detrended_fluctuation_analysis

    In stochastic processes, chaos theory and time series analysis, detrended fluctuation analysis (DFA) is a method for determining the statistical self-affinity of a signal. It is useful for analysing time series that appear to be long-memory processes (diverging correlation time, e.g. power-law decaying autocorrelation function) or 1/f noise.

  7. Autoregressive model - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_model

    The notation () indicates an autoregressive model of order p.The AR(p) model is defined as = = + where , …, are the parameters of the model, and is white noise. [1] [2] This can be equivalently written using the backshift operator B as

  8. Whitening transformation - Wikipedia

    en.wikipedia.org/wiki/Whitening_transformation

    The transformation is called "whitening" because it changes the input vector into a white noise vector. Several other transformations are closely related to whitening: the decorrelation transform removes only the correlations but leaves variances intact, the standardization transform sets variances to 1 but leaves correlations intact,

  9. White noise analysis - Wikipedia

    en.wikipedia.org/wiki/White_noise_analysis

    First, white noise is a generalized stochastic process with independent values at each time. [12] Hence it plays the role of a generalized system of independent coordinates, in the sense that in various contexts it has been fruitful to express more general processes occurring e.g. in engineering or mathematical finance, in terms of white noise.