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cross-correlation
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cross-correlation

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Also known as cross-correlation function

thumb|400px|Visual comparison of convolution, cross-correlation and [[autocorrelation. For the operations involving function , and assuming the height of is 1.0, the value of the result at 5 different points is indicated by the shaded area below each point. Also, the vertical symmetry of is the reason f*g and f \star g are identical in this example.]]

~18 min read

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24 sections
Contents
  • Cross-correlation of deterministic signals
  • Explanation
  • Properties
  • Cross-correlation of random vectors
  • Definition
  • Example
  • Definition for complex random vectors
  • Cross-correlation of stochastic processes
  • Cross-correlation function
  • Cross-covariance function
  • Definition for wide-sense stationary stochastic process
  • Cross-correlation function
  • Cross-covariance function
  • Normalization
  • Properties
  • Symmetry property
  • Time delay analysis
  • Zero-normalized cross-correlation (ZNCC)
  • Normalized cross-correlation (NCC)
  • Nonlinear systems
  • See also
  • References
  • Further reading
  • External links

thumb|400px|Visual comparison of convolution, cross-correlation and [[autocorrelation. For the operations involving function , and assuming the height of is 1.0, the value of the result at 5 different points is indicated by the shaded area below each point. Also, the vertical symmetry of is the reason f*g and f \star g are identical in this example.]]

In signal processing, cross-correlation is a measure of similarity of two series as a function of the displacement of one relative to the other. This is also known as a sliding dot product or sliding inner-product. It is commonly used for searching a long signal for a shorter, known feature. It has applications in pattern recognition, single particle analysis, electron tomography, averaging, cryptanalysis, and neurophysiology. The cross-correlation is similar in nature to the convolution of two functions. In an autocorrelation, which is the cross-correlation of a signal with itself, there will always be a peak at a lag of zero, and its size will be the signal energy.

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