öz ilinti

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Definition von öz ilinti im Türkisch Englisch wörterbuch

autocorrelation

The cross-correlation of a signal with itself: the correlation between values of a signal in successive time periods

Autocorrelation is a mathematical tool used frequently in signal processing for analysing functions or series of values, such as time domain signals. Informally, it is a measure of how well a signal matches a time-shifted version of itself, as a function of the amount of time shift. More precisely, it is the cross-correlation of a signal with itself. Autocorrelation is useful for finding repeating patterns in a signal, such as determining the presence of a periodic signal which has been buried under noise, or identifying the missing fundamental frequency in a signal implied by its harmonic frequencies

The simple linear correlation of a time series with its own past; that is, the correlation of the sequence of values x(t) with the sequence of values x(t ) occurring units of time later The time displacement is called the lag The autocorrelation function is the autocorrelation for variable lag The autocorrelation coefficient is the product-moment correlation coefficient that relates the variables x(t) and x(t ) See serial correlation

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Correlation of the error terms from different observations of the same variable Also called serial correlation

The correlation of a variable with itself over successive time intervals

the correlations among numbers ordered in a series

The autocorrelation of an object A, known as the Patterson map in crystallography, is the correlation product of A with itself: A • A By the convolution theorem, the Fourier transform of the autocorrelation of A is the squared Fourier modulus of A: F( A • A ) = F(A)* F(A) = |F(A)| 2 The autocorrelation is therefore an equivalent way of representing Fourier modulus data

The problem of interdependence among successive values of the disturbance term The problem with autocorrelation concerns the variance of our estimator

Statistical concept expressing the degree to which the value of an attribute at spatially adjacent points covaries with the distance separating the points

The correlation of a signal with itself, as opposed to the cross correlation between two different signals The Fourier transform of the autocorrelation function of a signal is the signal's power spectrum This relationship provides the basis for autocorrelation spectrometers

Correlation of successive residuals This condition frequently occurs when time is involved in the analysis

At lag k, the correlation between the data value at time t and the data value at time (t-k) Autocorrelations are often calculated for time series data to determine how the correlation between data values varies with the distance or time "lag" between them For each autocorrelation, a corresponding standard error is calculated If the time series is random, all of the autocorrelations should be within approximately 0 +/- 2 standard errors Estimates extending beyond this distance indicate significant correlation between data values separated by the indicated time lag

This occurs when later variables in a time series are correlated with earlier variables

The comparision of a signal with a previous signal in order to pick out repetitive features

The similarity or correlation between a sequence of data and itself, at different offsets Clearly, at zero offset, any data sequence is maximally correlated to itself But if one version is rotated or given a circular shift of n positions, there may not be much correlation at all, especially in noise signals The autocorrelation result is typically a correlation computed for every possible sequence offset, with the data considered repetitive or circular Noise data are not repetitive, but the characteristics of the generation tend to be constant and we can treat the result as a circular array without much offense to the underlying requirements

The correlation between the values of a time series and previous values of the same time series

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