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[12] [13] [clarification needed] After calculating the cross-correlation between the two signals, the maximum (or minimum if the signals are negatively correlated) of the cross-correlation function indicates the point in time where the signals are best aligned; i.e., the time delay between the two signals is determined by the argument of the ...
Some examples where Barker code is used are: pet and livestock tracking, bar code scanners, inventory management, vehicle, parcel, asset and equipment tracking, inventory control, cargo and supply chain logistics. [25] It is also used extensively for Intelligent Transport Systems (ITS) i.e. for vehicle guidance [26]
For example, in time series analysis, a plot of the sample autocorrelations versus (the time lags) is an autocorrelogram. If cross-correlation is plotted, the result is called a cross-correlogram . The correlogram is a commonly used tool for checking randomness in a data set .
Kasami sequences have good cross-correlation values approaching the Welch lower bound. There are two classes of Kasami sequences—the small set and the large set. There are two classes of Kasami sequences—the small set and the large set.
The highest absolute cross-correlation in this set of codes is 2 (n+2)/2 + 1 for even n and 2 (n+1)/2 + 1 for odd n. The exclusive or of two different Gold codes from the same set is another Gold code in some phase. Within a set of Gold codes about half of the codes are balanced – the number of ones and zeros differs by only one. [5]
The cross-correlation matrix of two random vectors is a matrix containing as elements the cross-correlations of all pairs of elements of the random vectors. The cross-correlation matrix is used in various digital signal processing algorithms.
The correlator has an input signal which is multiplied by some filter in the Fourier domain. An example filter is the matched filter which uses the cross correlation of the two signals. The cross correlation or correlation plane, (,) of a 2D signal (,) with (,) is
The r* cross-correlation metric is based on the variance metrics of SSIM. It's defined as r*(x, y) = σ xy / σ x σ y when σ x σ y ≠ 0, 1 when both standard deviations are zero, and 0 when only one is zero. It has found use in analyzing human response to contrast-detail phantoms. [18] SSIM has also been used on the gradient of ...