Difference between revisions of "Cross-correlation"
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Latest revision as of 15:11, 24 August 2016
In signal processing, cross-correlation is a measure of similarity of two series as a function of the lag of one relative to the other. This is also known as a sliding dot product or sliding inner-product.
Description
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.
See also
- Autocorrelation
- Autocovariance
- Coherence
- Convolution - a mathematical operation on two functions (f and g).
- Correlation
- Correlation function
- Cross-covariance
- Cross-spectrum
- Covariance mapping
- Digital image correlation
- Phase correlation
- Scaled correlation
- Signal processing
- Spectral density
- Wiener–Khinchin theorem
External links
- Cross-correlation @ Wikipedia
